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INHIBITING BREAST CANCER PROGRESSION
BY TARGETING SND1
USING A NOVEL PEPTIDE
IDENTIFIED FROM PHAGE DISPLAY
LI PENG
PhD
The Hong Kong Polytechnic University
2019
The Hong Kong Polytechnic University
Department of Applied Biology and Chemical
Technology
INHIBITING BREAST CANCER PROGRESSION
BY TARGETING SND1
USING A NOVEL PEPTIDE
IDENTIFIED FROM PHAGE DISPLAY
LI Peng
A thesis submitted in partial fulfillment of the requirements for
the degree of Doctor of Philosophy
Jan 2019
I
CERTIFICATE OF ORIGINALITY
I hereby declare that this thesis is my own work and that, to the best of
my knowledge and belief, it reproduces no material previously published
or written nor material which has been accepted for the award of any
other degree or diploma, except where due acknowledgement has been
made in the text.
LI Peng
Signature:
II
Abstract
Breast cancer is the most common cancer in women, causing 626,679
deaths worldwide in 2018. SND1 is a multifunctional oncoprotein
overexpressed in almost all cancers, especially in advanced and
metastatic cases. SND1-MTDH interaction contributes to the initiation
and progression of breast cancer, making it a promising target for breast
cancer treatment.
In this study, recombinant SN1/2 domain of SND1 was expressed in E.coli
and purified with HisTrap affinity column. SN1/2 was used as bait in a
phage display screening. After 4 rounds of screening, 20 phages were
randomly picked and sequenced. Amino acids W and Y were found to be
highly enriched in these phages. The most repeated peptide 4-2 was
demonstrated to have high binding affinity towards SN1/2. Peptide 4-2
could disrupt 22-mer MTDH peptide from interacting with SN1/2 in ELISA
assay and could also disrupt SND1-MTDH full-length protein interaction
in co-immunoprecipitation assay.
An RR-TAT cell penetrating peptide was attached to the N-terminus of
peptide 4-2 to generate CPP-4-2 peptide. CPP-4-2 peptide could
penetrate and preferentially kill breast cancer cells by inducing apoptosis
compared to other cancer types or normal cells. Mechanistic
investigation suggested that peptide 4-2 could interact with SND1 and
disrupt SND1-MTDH interaction, which probably lead to the degradation
III
of SND1. Overexpression of SND1 could reduce the cytotoxicity of
peptide 4-2 to breast cancer cells, indicating that the disruption of
SND1-MTDH interaction and subsequent degradation of SND1 by peptide
4-2 was the possible reason for breast cancer cell death.
It was found that peptide 4-2 could regulate Akt pathway by upregulating
p-Akt S473 and degrading Akt. The degradation of Akt by peptide 4-2
was proteasome-dependent and was partially dependent on the
phosphorylation of Akt at S473. On the other hand, peptide 4-2 could
also regulate another SND1 downstream target NF-κB2 by enhancing the
transcription of pro-apoptotic NF-κB2. The degradation of Akt and the
enhanced transcription of NF-κB2 induced by peptide 4-2 might be the
reasons for breast cancer cell death.
Mutational analysis suggested that W10 but not Y4 or Y11 was essential
in the activities of peptide 4-2, including cytotoxicity, SND1-interaction,
SND1 downregulation, Akt degradation and NF-κB2 activation.
In summary, peptide 4-2 selectively killed breast cancer cells by inducing
apoptosis possibly through interacting with SND1, disrupting
SND1-MTDH interaction and inducing SND1 degradation. Peptide 4-2
could also affect SND1 downstream targets, Akt and NF-κB2 by degrading
Akt and enhancing the transcription of pro-apoptotic NF-κB2, which
possibly lead to breast cancer cell death. W10 rather than Y4 or Y11 was
the essential amino acid in the activities of peptide 4-2.
IV
Acknowledgement
I would like to express my sincere appreciation to my supervisor Prof.
Larry Chow, who gave me a precious opportunity to study in his lab in
PolyU. More importantly, he gave me a lot of professional guidance,
invaluable suggestions and generous encouragement in accomplishing
the project. I really appreciate the time and efforts he paid in my project
during my PhD study.
Sincere thanks are also given to Prof. Bill Chan who well knows the
progress of my project and gives many constructive suggestions to my
project.
Next I would like to give thanks to all the members in LC group and also
all the technicians in ABCT department. Thanks for their kindness in
teaching me the experimental techniques and helping me to overcome
so many difficulties. Special thanks are given to Miss Chen Teng, Dr. Choy
Kitying, Mr. Kalvin Chow, Mr. Zhu Xuezhen and Dr. Iris Wong for their very
useful suggestions and kindly help in designing and conducting the
experiments.
I would also like to thank Prof. Ruben Abagyan from Skaggs School of
Pharmacy, UC San Diego for giving me the opportunity to have a very
impressive and unforgettable three-month study in his lab. I learned a lot
not only from his very professional guidance but also his kindness when
he works with people. Special thanks are given to Mr. Da Shi, PhD
V
student from Prof. Abgyan’ lab to thank for his very selfless help in
teaching and helping me to accomplish the molecular docking
experiment.
Great thanks are also given to Ms. Josephine Leung who very nicely helps
me to correct my PhD thesis.
Again, thank you all for the unforgettable help during my PhD study!
VI
Table of contents
CERTIFICATE OF ORIGINALITY ................................................................ I
ABSTRACT ............................................................................................. II
ACKNOWLEDGEMENT ......................................................................... IV
TABLE OF CONTENTS ........................................................................... VI
LIST OF FIGURES ................................................................................ XIII
LIST OF TABLES ................................................................................ XVIII
LIST OF ABBREVIATIONS.................................................................... XIX
CHAPTER 1 INTRODUCTION .................................................................. 1
1.1 BACKGROUND ..................................................................................... 1
1.1.1 Breast cancer ............................................................................ 1
1.1.1.1 Pathology of breast cancer .................................................. 1
1.1.1.2 Cell origin of Breast cancer ................................................. 4
1.1.1.3 Breast cancer metastasis ..................................................... 7
1.1.1.4 Classification of breast cancer ............................................. 9
1.1.1.5 Treatment of breast cancer ............................................... 16
1.1.1.6 Breast cancer recurrence .................................................. 20
1.1.2 SND1 ....................................................................................... 22
1.1.2.1 Identification of SND1 ....................................................... 23
1.1.2.2 Structure of SND1 ............................................................. 23
VII
1.1.2.3 Multifunctional roles of SND1 ........................................... 27
1.1.2.4 Role of SND1 in different cancer types .............................. 33
1.1.2.5 Current inhibitors of SND1 ................................................ 44
1.1.3 MTDH ..................................................................................... 45
1.1.3.1 MTDH and poor clinical outcomes .................................... 46
1.1.3.2 MTDH structure ................................................................ 46
1.1.3.3 MTDH promoted cell proliferation and metastasis of breast
cancer ........................................................................................... 47
1.1.3.4 MTDH promoted angiogenesis of breast cancer ............... 48
1.1.3.5 MTDH promoted tumor initiation and metastasis in
transgenic mouse model .............................................................. 48
1.2 OBJECTIVES ...................................................................................... 50
CHAPTER 2 SCREENING OF SND1-INTERACTING PEPTIDES USING PHAGE
DISPLAY .............................................................................................. 51
2.1 ABSTRACT ........................................................................................ 51
2.2 INTRODUCTION .................................................................................. 52
2.2.1 Phage display technology ........................................................ 52
2.2.2 SND1-MTDH interaction promoted breast cancer initiation and
progression ...................................................................................... 54
2.2.3 Size exclusion chromatography and multi-angle light scattering
technology ....................................................................................... 56
2.3 METHODOLOGY ................................................................................. 56
VIII
2.3.1 Expression and Purification of SN1/2 ...................................... 56
2.3.2 Screening of a 12-mer phage display library based on SN1/2 . 58
2.3.3 Phage amplification, titering and sequencing ......................... 59
2.3.4 Phage ELISA and peptide ELISA ............................................... 60
2.3.5 SEC-MALS................................................................................ 61
2.3.6 Peptide synthesis .................................................................... 61
2.3.7 Co-immunoprecipitation assay ............................................... 62
2.4 RESULTS ........................................................................................... 63
2.4.1 Expression and purification of GST-6XHis-SN1/2 ..................... 63
2.4.2 SEC-MALS confirmed the monomeric status of SN1/2 ............ 67
2.4.3 Phage display screening of peptides binding to SN1/2 ............ 68
2.4.4 Binding affinity of individual phages to SN1/2 ........................ 70
2.4.5 22-mer 5-FAM-MTDH peptide binding to SN1/2 ..................... 72
2.4.6 Peptide candidates competed with MTDH binding to SN1/2 .. 74
2.4.7 Peptide 4-2 disrupted full-length SND1-MTDH complex ......... 76
2.5 DISCUSSION ...................................................................................... 79
2.5.1 Unusually high percentage of tryptophan in SN1/2 binding
peptides .......................................................................................... 79
2.5.2 Peptide 4-2 could disrupt SND1-MTDH interaction ................. 79
2.5.3 Peptide binding affinity towards SN1/2 (phage ELISA)
corresponded to the ability of disrupting 5-FAM-MTDH-SN1/2
interaction ....................................................................................... 80
IX
2.5.4 5-FAM-MTDH scrambled peptide showed mild binding affinity
towards SN1/2 domain of SND1 ...................................................... 81
CHAPTER 3 CYTOTOXIC EFFECT OF CPP-4-2 TO BREAST CANCER CELLS
AND ITS POTENTIAL MECHANISM ....................................................... 82
3.1 ABSTRACT ........................................................................................ 82
3.2 INTRODUCTION .................................................................................. 85
3.2.1 Cell-penetrating peptides ....................................................... 85
3.2.2 Akt signaling ........................................................................... 87
3.2.2.1 Activation of Akt signaling ................................................. 88
3.2.2.2 Akt degradation pathways ................................................ 91
3.2.3 NF-κB signaling ....................................................................... 93
NF-κB2/p100 ................................................................................ 94
3.3 METHODOLOGY ................................................................................. 96
3.3.1 Cell seeding, peptide treatment and MTS assay ...................... 96
3.3.2 Cell culture, peptide treatment and cell transfection .............. 96
3.3.3 Biotinylated 4-2 peptide pull-down assay ............................... 98
3.3.4 Peptide synthesis .................................................................... 98
3.3.5 Western blot ........................................................................... 98
3.3.6 In silico docking of peptide 4-2 to SN1/2................................. 99
3.3.6.1 Determination of the binding pockets on SN1/2 ............... 99
3.3.6.2 Peptide sampling using Monte Carlo method ................. 100
3.3.7 Proteomics analysis .............................................................. 100
X
3.3.8 RNA extraction and Real-time PCR ........................................ 101
3.3.9 5-FAM-CPP-4-2 accumulation assay and flow cytometry ...... 102
3.3.10 Apoptosis assay and Flow cytometry .................................. 103
3.4 RESULTS ......................................................................................... 104
3.4.1 CPP-4-2 preferentially killed breast cancer cells .................... 104
3.4.2 Investigation of the essential amino acids of CPP-4-2 in
cytotoxicity .................................................................................... 107
3.4.3 CPP-4-2 killed breast cancer cells by inducing apoptosis ....... 109
3.4.4 Biotinylated 4-2 peptide pulled down full-length SND1 ........ 110
3.4.5 Investigation of the essential amino acids of peptide 4-2 in
SND1 interaction ........................................................................... 111
3.4.6 CPP-4-2 downregulated SND1 of breast cancer cells ............. 114
3.4.7 Overexpression of SND1 reduced the cytotoxicity of CPP-4-2 to
breast cancer cells ......................................................................... 116
3.4.8 CPP-4-2 affected Akt pathway by upregulating p-Akt and
downregulating Akt ....................................................................... 118
3.4.9 The activation of Akt by CPP-4-2 was transient ..................... 122
3.4.10 The activation of Akt by CPP-4-2 was not transmitted to its
downstream target mTORC1 ......................................................... 123
3.4.11 CPP-4-2 mediated degradation of Akt was
proteasome-dependent, the phosphorylation of Akt partially
contributed to the degradation of Akt ........................................... 124
XI
3.4.12 CPP-4-2 affected important cell survival pathway of
MDA-MB-231-GFP-Red-FLuc cells in proteomics study .................. 127
3.4.13 CPP-4-2 upregulated pro-apoptotic NF-κB2 but did not affect
EP400 or ITGB4 .............................................................................. 132
3.4.14 In silico docking of peptide 4-2 to SN1/2 ............................. 136
3.5 DISCUSSION .................................................................................... 139
3.5.1 Construction of CPP-4-2 peptide ........................................... 139
3.5.2 In silico docking of peptide 4-2 to SN1/2............................... 139
3.5.3 MTS, Flow cytometry and high content screening ................ 140
3.5.4 CPP-4-2 preferentially killed breast cancer cells but not other
cancer types or mouse fibroblast................................................... 141
3.5.5 CPP-4-2 mediated SND1-dependent cytotoxicity in
MDA-MB-231-GFP-Red-FLuc cells .................................................. 142
3.5.6 Peptide 4-2 mediated disruption of SND1-MTDH interaction and
subsequent degradation of SND1 might be the reason for breast
cancer cell death ........................................................................... 143
3.5.7 CPP-4-2 might kill breast cancer cells by affecting Akt pathway
or by enhancing NF-κB2 transcription ............................................ 144
3.5.7.1 CPP-4-2 induced cytotoxicity probably through Akt pathway
................................................................................................... 145
3.5.7.2 CPP-4-2 killed breast cancer cells probably by enhancing the
transcription of NF-κB2 ............................................................... 146
XII
CHAPTER 4 LIMITATIONS AND FUTURE PERSPECTIVES ....................... 149
4.1 A novel SND1-interacting peptide that can disrupt SND1-MTDH
interaction ..................................................................................... 149
4.2 Peptide 4-2 shows preferential cytotoxicity towards breast cancer
cells ............................................................................................... 151
4.3 Mechanisms of the cytotoxicity of peptide 4-2 to breast cancer
cells ............................................................................................... 152
4.4 W10 is the essential amino acid in the activity of peptide 4-2 . 153
REFERENCE ....................................................................................... 155
XIII
List of figures
Figure 1.1 Age standardized rate of breast cancer incidence worldwide in
2018 (WHO, 2018) ................................................................................... 2
Figure 1.2 Age standardized rate of breast cancer mortality worldwide in
2018 (WHO, 2018) ................................................................................... 3
Figure 1.3 Cell origins of cancer from CSCs .............................................. 5
Figure 1.4 EMT and MET processes of cancer metastasis ........................ 8
Figure 1.5 TNM classification of tumors of the breast ........................... 15
Figure 1.6 CSCs lead to breast cancer recurrence .................................. 21
Figure 1.7 Schematic representation of the secondary structure of SND1
.............................................................................................................. 24
Figure 1.8 Ribbon model of the crystal structure of SN3/4-Tudor-SN5
domains of SND1 (PDB: 3BDL) ............................................................... 26
Figure 1.9 Co-crystal structure of SN1/2 domain of SND1 with an
11-residue MTDH peptide (PDB: 4QMG) ............................................... 27
Figure 1.10 The process of RNA interference ......................................... 31
Figure 1.11 Breast cancer genomics data of SND1 (TCGA) ..................... 35
Figure 1.12 High SND1 expression correlated with increased risk of lung
metastasis of breast cancer ................................................................... 37
Figure 1.13 Kaplan-Meier survival curves based on SND1 expression in
IDC patients ........................................................................................... 38
Figure 1.14 Kaplan-Meier survival curves based on SND1 expression in
XIV
lymph-node-positive breast cancer patients.......................................... 39
Figure 1.15 A schematic diagram of MTDH protein and its postulated
functional domains ................................................................................ 47
Figure 2.1 Work flow of Chapter 2 ......................................................... 52
Figure 2.2 Co-crystal structure of SN1/2 domain of SND1 with an
11-residue MTDH peptide (PDB: 4QMG) ............................................... 55
Figure 2.3 Construction of SN1/2 expression vector .............................. 57
Figure 2.4 FPLC purification of GST-6XHis-SN1/2 recombinant protein .. 64
Figure 2.5 Purification of GST-6XHis-SN1/2 recombinant protein .......... 65
Figure 2.6 FPLC purification of SN1/2 protein after HRV 3C protease
digestion ................................................................................................ 66
Figure 2.7 Purification of SN1/2 protein after HRV 3C digestion ............ 67
Figure 2.8 SEC-MALS spectrum confirmed the monomeric status of
purified SN1/2 ....................................................................................... 68
Figure 2.9 Determination of binding affinity of phages towards SN1/2
using ELISA ............................................................................................ 71
Figure 2.10 ELISA study of 5-FAM-MTDH peptide binding to SN1/2 ...... 73
Figure 2.11 ELISA study of peptides competed with 5-FAM-MTDH peptide
binding to SN1/2 ................................................................................... 74
Figure 2.12 Peptide 4-2, 4-8 and 4-13 disrupted 5-FAM-MTDH-SN1/2
interaction ............................................................................................. 75
Figure 2.13 Peptide 4-16 and 4-19 enhanced 5-FAM-MTDH-SN1/2
XV
interaction ............................................................................................. 75
Figure 2.14 Peptide 4-5 enhanced 5-FAM-MTDH-SN1/2 interaction ...... 76
Figure 2.15 co-IP of MTDH by c-Myc-SND1 using c-Myc antibody ......... 77
Figure 2.16 Disruption of full-length SND1-MTDH complex by peptide 4-2
(c-Myc co-IP) ......................................................................................... 77
Figure 2.17 co-IP of SND1 by V5-MTDH using V5 antibody .................... 78
Figure 2.18 Disruption of full-length SND1-MTDH complex by peptide 4-2
(V5 co-IP) ............................................................................................... 78
Figure 3.1 Molecular mechanisms of Akt regulation .............................. 90
Figure 3.2 Secondary structures of p100 and p52 .................................. 94
Figure 3.3 Maps of pCMV6-Entry-SND1-cMyc-DDK plasmid and
pLX304-MTDH-V5 plasmid ..................................................................... 97
Figure 3.4 CPP-4-2 preferentially killed breast cancer cell lines ........... 105
Figure 3.5 CPP-4-2 accumulated equally among different cell lines ..... 106
Figure 3.6 Expression level of SND1 in different cell lines .................... 107
Figure 3.7 Cytotoxicity of CPP-4-2 and its mutants on
MDA-MB-231-GFP-Red-FLuc cells ........................................................ 108
Figure 3.8 CPP-4-2 induces apoptosis of breast cancer cells ................ 109
Figure 3.9 Biotinylated 4-2 peptide pulled down SND1 (diagram) ....... 110
Figure 3.10 Biotinylated 4-2 peptide pulled down SND1...................... 111
Figure 3.11 4-2 and its mutant peptides competed with the pull down of
SND1 by biotinylated 4-2 peptide (diagram) ........................................ 113
XVI
Figure 3.12 W10 was the essential amino acid in SND1-interaction .... 113
Figure 3.13 CPP-4-2 downregulated SND1 in MDA-MB-231-GFP-Red-FLuc
cells ..................................................................................................... 115
Figure 3.14 CPP-4-2 downregulated SND1 in breast cancer cells ......... 116
Figure 3.15 Overexpression of SND1 in MDA-MB-231-GFP-Red-FLuc cell
............................................................................................................ 117
Figure 3.16 SND1 overexpression reduced the cytotoxicity of CPP-4-2 to
MDA-MB-231-GFP-Red-FLuc cells ........................................................ 117
Figure 3.17 CPP-4-2 specifically affected Akt pathway by upregulating
p-Akt s473 and downregulating total Akt in MDA-MB-231-GFP-Red-FLuc
cells ..................................................................................................... 119
Figure 3.18 Quantization of pAkt S473 and Akt expression after
treatment with CPP-4-2 ....................................................................... 119
Figure 3.19 CPP-4-2 specifically affected Akt pathway in breast cancer
cells ..................................................................................................... 121
Figure 3.20 The activation of Akt by CPP-4-2 was transient ................. 122
Figure 3.21 CPP-4-2 did not activate mTORC1 ..................................... 123
Figure 3.22 CPP-4-2 induced proteasome-dependent degradation of Akt
............................................................................................................ 125
Figure 3.23 Akt degradation induced by CPP-4-2 was partially contributed
by the phosphorylation of Akt at S473 ................................................ 126
Figure 3.24 Sequence alignment of peptide 4-2 to ITGB4 .................... 130
XVII
Figure 3.25 Top 8 pathways most probably affected by CPP-4-2
determined by proteomics study ......................................................... 131
Figure 3.26 CPP-4-2 did not change the mRNA levels of EP400 or ITGB4
............................................................................................................ 132
Figure 3.27 CPP-4-2 upregulated mRNA levels of NF-κB2 and its family
members ............................................................................................. 134
Figure 3.28 mRNA levels of Bax and BCL2 after peptide treatment ..... 135
Figure 3.29 Five tentative binding sites on SN1/2 and Box1................. 136
Figure 3.30 Most possible conformation of 4-2 interacted with SN1/2 138
Figure 3.31 A proposed pathway of peptide 4-2 mediating breast cancer
cell death ............................................................................................. 148
XVIII
List of tables
Table 1.1 A summary of breast cancer molecular subtypes ................... 11
Table 2.1 SN1/2 binding peptides identified from phage display ........... 69
Table 3.1 Examples of CPPs and their sequences, origins, and
physical–chemical properties ................................................................ 86
Table 3.2 IC50s of CPP-4-2 of different cell lines ................................... 105
Table 3.3 Cytotoxicity of CPP-4-2 and its mutants on
MDA-MB-231-GFP-Red-FLuc cells ........................................................ 108
Table 3.4 Sequences and cytotoxicity of peptide 4-2 and its mutants .. 112
Table 3.5 Cytotoxicity and SND1 binding ability of peptide 4-2 and its
mutants ............................................................................................... 114
Table 3.6 Cytotoxicity of peptides and their ability to interact with SND1
or downregulate SND1 ........................................................................ 115
Table 3.7 Cytotoxicity of peptides and their ability to interact with SND1,
downregulate SND1 or affect Akt pathway .......................................... 120
Table 3.8 Proteomics study of differentially-expressed proteins after
treatment with CPP-4-2 and its mutants ............................................. 128
Table 3.9 Possible conformations of peptide 4-2 binding to SN1/2 ...... 137
Table 3.10 A summary of the characteristics of CPP-4-2 and its mutants
............................................................................................................ 145
Table 4.1 SND1 binding partners ......................................................... 150
XIX
List of Abbreviations
BCRP Breast cancer resistant protein
BRCA1 Breast cancer susceptibility gene 1
CHIP Chromatin immunoprecipitation
CPP Cell-penetrating peptides
CSC Cancer stem cells
CTC Circulating tumor cells
DCIS Ductal carcinoma in situ
dsRNA Double-stranded RNA
dTp Deoxythymidine 3’, 5’-bisphosphate
EBNA2 Epstein-Barr virus nuclear antigen 2
E.coli Escherichia coli
ELISA Enzyme-linked immunosorbent assay
EMT Epithelial-mesenchymal transition
FoxO Forkhead Box O
FPLC Fast Protein Liquid Chromatography
GPCR G-protein-coupled receptors
GSK3 Glycogen synthase kinase 3
GST Glutathione S-transferase
HCC Hepatocellular carcinoma
HRV Human rhinovirus
ICM Internal Coordinate Mechanics
XX
IDC Invasive ductal carcinoma
IPA Ingenuity Pathway Analysis
ITGB4 Integrin, beta 4
MALS Multi-angle light scattering
MET Mesenchymal-epithelial transition
MGLL Monoglyceride Lipase
MTDH Metastasis adhesion protein, Metadherin
mTOR Mechanistic target of rapamycin
NF-κB Nuclear factor-kappaB
NLS Nuclear localization signals
NSCLC Non-small cell lung cancer
NTA Nitrilotriacetic acid
OD Optical density
PDK1 Phosphoinositide-dependent protein kinase 1
EP400 E1A-binding protein p400
pI Isoelectric point
PI3K Phosphoinositide-3-kinase
PIP3 Phosphatidylinositol 3-phosphate
PIWIL1 Piwi-like protein 1
PKB Protein kinase B
PMS Phenazine methyl sulfate
RISC RNA-induced silencing complex
XXI
RNAi RNA interference
RTK Receptor Tyrosine kinase
siRNA Small interfering RNA
SEC Size exclusion chromatography
SG Stress granule
SN Staphylococcal nuclease
SND1 Staphylococcal nuclease domain-containing protein 1
snRNP Small nuclear ribonucleoprotien
STAT Signal transducer and activator of transcription
TGFβ Transforming growth factor β
TMD Transmembrane domain
TNM Tumor Node Metastasis
TTC3 Tetratricopeptide repeat domain 3
ZEB1 Zinc finger E-box binding homeobox 1
1
Chapter 1 Introduction
1.1 Background
1.1.1 Breast cancer
1.1.1.1 Pathology of breast cancer
Breast cancer was the second most common cancer in the world and the
most common cancer among women, with an estimation of 2.09 million
new cases worldwide in 2018. The incidence rate varied by almost three
folds across different parts of the world, ranging from <24.8 cases per
100,000 in the South-Central Africa to 72.9 cases per 100,000 in
Australia/New Zealand, Europe and Northern America (Figure 1.1.a and
b) (WHO, 2018). Mortality rate of breast cancer was ranked number 5,
with an annual death rate of 626,679 in the world in 2018. The regional
difference in mortality rate was relatively small compared to the
incidence rate, possibly due to the high survival rate of breast cancer
patients in the developed world (Figure 1.2.a and b) (WHO, 2018).
2
Figure 1.1 Age standardized rate of breast cancer incidence worldwide
in 2018 (WHO, 2018)
ASR: Age standardized rate; Highest ASR (~90 per 100,000) of breast cancer incidence
happened in Australia/New Zealand, Europe and Northern America; Lowest SAR
(25.9 per 100,000) of breast cancer incidence happened in South-Central Africa.
a)
b)
3
Figure 1.2 Age standardized rate of breast cancer mortality worldwide
in 2018 (WHO, 2018)
ASR: Age standardized rate; ASR of breast cancer mortality did not vary a lot across
the world (8.6-25.5 cases per 100,000), though ASR of breast cancer incidence varied
significantly (25.9-94.2 cases per 100,000).
a)
b)
a)
4
1.1.1.2 Cell origin of Breast cancer
Breast cancer was a very heterogeneous disease, involving many
different types of cells with different biological properties (Al-Hajj et al.,
2003). There were two generally-accepted hypotheses on the cellular
origin of breast cancer.
In one theory, cancer was believed to originate from genetic mutations.
An accumulation of a large number of mutations resulted in an alteration
of complex internal signaling in cells. The accumulation of these genetic
abnormalities resulted in the development of a colony of cells which are
pathologically abnormal or malignant (Wren, 2007).
BRCA1 or BRCA2 gene, two predisposing genes for breast cancer
development, was found to be mutated in 5-10% of all newly diagnosed
breast cancers in the western world (Peshkin et al., 2010). Women with
an inherited BRCA1 mutation would have a lifetime risk of 65-80% of
developing breast cancer, and those with an inherited BRCA2 mutation
would have 45-85% risk of developing breast malignancy (Balmana et al.,
2009). Besides the BRCA genes, other genes such as TP53, PTEN, CDH11
and STK11 were also found to be associated with breast cancer as well
(Peng et al., 2016).
The second theory postulated that tumor was consisted of
heterogeneous cancer cells that had different functions during
tumorigenesis. The development of cancer was driven by a specialized
5
subset of cells with self-renewal and tumor-initiating properties. Most
likely they were generated from normal stem cells or progenitor cells
within tissues after oncogenic hit (Figure 1.3) (Papaccio et al., 2017b).
Although there were different opinions on how breast cancer initiated,
more and more recent research findings supported the theory that
cancer was caused by a small population of cancer cells called cancer
stem cells (CSCs), which accounted for only 1-5% of tumor cells (Al-Hajj
et al., 2003).
Figure 1.3 Cell origins of cancer from CSCs
In normal state, progenitor cells as immediate descendants of stem cells would
differentiate into well-differentiated cells (a→b→c). CSCs originated from stem cells
or progenitor cells after oncogenic hit and subsequently developed into tumors (a→
d→e). Traditional therapy of cancer such as chemotherapy killed differentiated
cancer cells instead of CSCs. The remaining CSCs would lead to metastasis or
recurrence (f). This figure was adapted from (Papaccio et al., 2017a).
6
CSCs had the ability to initiate tumors from a limited number of cells
after being injected into immunocompromised mice (Economopoulou et
al., 2012). According to CSC theory, tumors were derived from mutated
tissue stem cells which had an infinite capability of self-renewal. After
generating daughter cells from asymmetrical division, one daughter cell
kept the intrinsic ability of initiating tumors while the other would
differentiate and proliferate into tumors. As a result, in tumor, there
were a small population of CSCs remaining with stem cell like properties
and a large number of cancer cells undergoing rapid proliferation (Wicha
et al., 2006).
This small population of CSCs showed very high invasive property, clonal
evolution, and dormancy. They were also demonstrated to be capable of
promoting blood vessel formation. Besides the capability of triggering
tumorigenesis, CSCs could also contribute to cancer progression,
metastasis and recurrence (Economopoulou et al., 2012). Surface
markers like CD44+/CD24-/low and aldehyde dehydrogenase 1 high (ALDHhi)
were employed as surface markers of breast CSCs (Al-Hajj et al., 2003;
Ginestier et al., 2007). The proposal of CSC theory provided novel
insights on how cancer initiated, and more importantly, how cancer
could be treated and eventually eradicated in the future.
7
1.1.1.3 Breast cancer metastasis
Approximately 90% of cancer-related deaths were caused by cancer
metastases (Spano et al., 2012). Metastasis was a complicated multistep
biological event that involved a number of signaling pathways. Patients
with metastatic disease had poor prognosis of only 25% 5-year overall
survival rate (Rabbani and Mazar, 2007). Cancer metastasis required
cancer cells from primary tumor to spread to distant organs where they
could attach and proliferate into neoplastic foci (Steeg, 2006). The
traditional “seed and soil” theory of cancer metastasis was first proposed
in 1889 by Stephen Paget (Paget, 1989). The cascade of metastasis
events happened through the following steps as shown in Figure 1.4,
mainly through two opposite processes: epithelial-mesenchymal
transition (EMT) and mesenchymal-epithelial transition (MET).
8
Figure 1.4 EMT and MET processes of cancer metastasis
Cancer cells from the primary tumor migrated to the distant metastatic site through
the following processes (Kozlowski et al., 2015): a) angiogenesis, b) escape of tumor
cells from the primary tumor, c) migration through the basement membrane and the
extracellular matrix around the tumor, d) invasion through the basement membrane
of local blood vessels or lymphatics, e) intravasation of the tumor cells into blood or
lymphatic vessels, f) homing of circulating tumor cells onto the endothelium of
capillaries of distant organs, g) extravasation of tumor cells through endothelial cells,
basement membrane and tissue of target organs, h) colonization of tumor cells at the
secondary neoplastic foci. This figure was adapted from (Samarasinghe, 2013).
Recent evidence strongly suggested that CSCs played an important role
in metastasis. Only a small population of circulating tumor cells (CTCs)
were sufficient to initiate metastasis, but the identification of this
subpopulation of cells remained elusive (Weiss, 1990).
Since CSCs had the ability to initiate tumor (Economopoulou et al., 2012),
b
e
f&g h
a
c&d
9
it was reasonable to hypothesize that CSCs were actually the very small
subpopulation of CTCs, with increasing evidence supporting this
hypothesis.
Firstly, data of 226 blood samples from cancer patients indicated the
majority of the CTCs exhibited EMT and CSC properties (Aktas et al.,
2009). Additional study of 1439 CTCs identified from 20 out of 30
patients suggested that 35.2% of the CTCs exhibited a CD44+/CD24-/low
breast CSC phenotype (Theodoropoulos et al., 2010) and these
CD44+/CD24-/low CSCs favored distant metastasis especially bone
metastasis (Abraham et al., 2005). Moreover, CD44+/CD24-/low breast
CSCs were found to be prevalent in metastatic pleural effusions from
patients with late-stage or recurrent breast cancer (Yu et al., 2007). Lastly,
in an immunohistochemistry study of 50 bone marrow specimens from
breast cancer patients, the percentage of CD44+/CD24-/low CSCs was
significantly increased from <10% in primary tumor to 72% in bone
marrow (Balic et al., 2006).
1.1.1.4 Classification of breast cancer
1.1.1.4.1 Histopathological classification of breast cancer
WHO recommended breast tumor to be classified from a
histopathological point of view. In the latest 4th edition of WHO
Classification of Tumor of the Breast, breast tumor was mainly divided
10
into the following categories: epithelial tumors, mesenchymal tumors,
fibroepithelial tumors, metastatic tumors and etc.
The largest category, epithelial tumor, could be further divided into
several subcategories: invasive breast carcinoma,
epithelial-myoepithelial tumors, precursor lesions, intraductal
proliferative lesions, papillary lesions, and benign epithelial proliferations.
WHO classification of breast tumor was very thorough and detailed;
while some of the subtypes of breast tumors were not very common.
The most common breast carcinomas were described in the following
parts.
Invasive ductal carcinoma (IDC), the most common subtype of invasive
breast carcinoma, accounted for 40-75% of breast cancer upon diagnosis
(Sunil R. Lakhani, 2012). Ductal carcinoma in situ (DCIS) was another
major subgroup of breast carcinoma which falled into the category of
precursor lesions. It was a noninvasive, potentially malignant, intraductal
proliferation of epithelial cells confined to the ducts and lobules. Death
caused by DCIS was extremely rare, usually due to the undetected
invasive component or recurrence (Makki, 2015; Sunil R. Lakhani, 2012).
1.1.1.4.2 Molecular classification of breast cancer
Heterogeneity in breast cancer was very common and it can potentially
affect the effectiveness of breast cancer therapy. Intra- and inter-tumor
11
heterogeneity were frequently seen in breast cancer as a result of
genetic or non-genetic alterations which potentially enhanced the
malignancy of cancer cells (Koren and Bentires-Alj, 2015). There were
many factors that might contribute to the heterogeneity of breast cancer,
such as differentiation state of cell-of-origin, cell plasticity and tumor cell
hierarchy and genetic evolution (Koren and Bentires-Alj, 2015).
A distinctive “molecular portrait” of breast cancer was discovered after
analyzing 456 cDNA clones of different breast cancer subtypes (Table 1.1)
(Dai et al., 2015).
Table 1.1 A summary of breast cancer molecular subtypes
Intrinsic subtype IHC status Grade Outcome Prevalence
Luminal A ER+/PR+, HER2-, Ki67- 1/2 Good 23.7%
Luminal B ER+/PR+, HER2-, Ki67+
ER+/PR+, HER2+, Ki67+
2/3 Intermediate
Poor
38.8%
14%
HER2
overexpression
ER-/PR-, HER2+ 2/3 Poor 11.2%
Basal ER-/PR-, HER2-, basal
marker+
3 Poor 12.3%
Normal-like ER+/PR+, HER2-, Ki67- 1/2/3 Intermediate 7.8%
IHC: immunohistochemistry; ER: estrogen receptor; PR: progesterone receptor; HER2:
human epidermal growth factor receptor 2; Ki67: cellular marker for proliferation.
This table was adapted from (Dai et al., 2015).
Luminal subtype of breast cancer
ER expression played a major role in determining the potential response
to hormone therapy of breast cancer. Hormone-dependent and
ER-positive luminal subtype of breast cancer accounted for
12
approximately 70% of all breast cancer cases (Lumachi et al., 2013). They
could be treated relatively easily with endocrine therapy and usually
with better outcomes. With the development of microarray technology,
breast cancer could be classified according to gene expression profiling,
which was especially useful for identifying markers associated with good
prognosis (Dai et al., 2015).
Sørlie et al reported the data reanalysis of the molecular portraits of 456
cDNA clones of breast cancer (Sorlie et al., 2001). A total of 23.7% of the
patient cohort of the luminal A subtype of breast cancer expressed
higher level of ER-related genes and a lower level of proliferative genes
compared with patients of the luminal B subtype of breast cancer. The
luminal A subtype breast cancer correlated with a lower grade exhibited
the best outcome among all the subtypes of breast cancer. Luminal B
(38.8%) and Luminal B-like (14%) cancers with Ki67-positive expression
showed intermediate to poor outcome involving higher grades (Table 1.1)
(Dai et al., 2015).
HER2-positive breast cancer
The HER2-positive subtype of breast cancer was ER- and PR- negative
with an incidence rate of 11.2% of all breast cancer cases (Table 1.1). It
was more likely to be Grade 3 breast cancer with poor prognosis.
Fortunately, this subtype of tumor was sensitive to chemotherapy with a
much higher response rate compared to luminal breast cancer (Brenton
13
et al., 2005). There were more treatment options for HER2 positive cases
than triple negative breast cancer such as trastuzumab, an antibody
against HER2, which was effective against HER2-positve breast cancer
(Dai et al., 2015).
Triple negative or basal-like breast cancer
Triple negative breast cancer (ER-, PR- and HER2-) accounted for 10-17%
of all breast cancer cases (Badve et al., 2011). Missing these receptors
made this type of cancer the most difficult to treat. This type of cancer
was more frequently found among younger patients (<50 years old) and
was much more aggressive and has poorer prognosis than any other
types of breast tumors (Badve et al., 2011).
The exact definition of basal-like breast cancer was controversial since
some groups define it using the microarray-based expression profiling
while others use immunohistochemical markers as surrogate markers.
From an immunohistochemical point of view, basal-like breast cancer
should be missing ER, PR or HER2 and has a high level of basal-like
markers such as CK5/6 and epidermal growth factor receptor (Badve et
al., 2011). Approximately 71% of triple-negative breast cancer was of
basal subtype according to gene expression profiling and 77% of the
basal subtype of breast cancer was determined as triple-negative
(Bertucci et al., 2008). Triple-negative breast cancer and basal-like breast
cancer were often used as synonymous since they shared numerous
14
similarities (Badve et al., 2011).
1.1.1.4.3 TNM classification of breast cancer
Since the introduction of the Tumor Node Metastasis (TNM) system by
Pierre Denoix in the 1940s, TNM has been providing an invaluable means
to describe the anatomic extent of cancer and to determine its stages
(Cserni et al., 2018). Unlike the anatomical classification based on
histology or molecular gene expression profiling, TNM classified tumors
by clinical presentation such as primary tumor, feature of regional lymph
nodes and distant metastasis of tumors (Sunil R. Lakhani, 2012). The 4th
edition of WHO Classification of Tumor of the Breast was shown in Figure
1.5 (Sunil R. Lakhani, 2012).
15
Figure 1.5 TNM classification of tumors of the breast
TNM classified tumors by primary tumor size, feature of regional lymph nodes, and
distant metastasis of tumors. This figure was adapted from (Sunil R. Lakhani, 2012).
16
1.1.1.5 Treatment of breast cancer
1.1.1.5.1 General treatment of breast cancer
General treatment of breast cancer included local treatment such as
surgery and radiation, systematic treatment such as chemotherapy,
hormone therapy and molecular targeted therapy. The choice of
treatment of breast cancer depended on the stage, molecular portrait
and aggressiveness of the disease.
Newly-diagnosed non-metastatic breast cancer cases could be divided
into two categories: early stage (I, IIA, T2N1) and locally advanced stage
(T3N0, IIIA to IIIC) (Alphonse Taghian, 2017). Early-stage cases should
undergo primary surgery followed by an optional radiation therapy.
Adjuvant systemic therapy might be offered depending on primary
tumor characteristics. Patients who were diagnosed with locally
advanced breast cancer would receive neoadjuvant systemic therapy to
induce tumor response before surgery. After the primary surgery, the
choice of adjuvant therapy (chemotherapy and/or endocrine therapy)
was guided by the clinical status and the characteristics of the tumor.
Approximately 5% of breast cancer patients were diagnosed with
metastasis at the initial presentation. Metastatic breast cancer was very
difficult to treat so the main goal of treatment was to prolong survival,
alleviate symptoms and improve the quality of life. Treatment of
17
metastatic breast cancer was a far more complicated task compared to
non-metastatic ones.
Daniel F Hayes has provided a thorough review of the treatments of
metastatic breast cancer (Hayes, 2018). In this review, disease
assessment of breast cancer was a very important procedure that would
guide the whole process of treatment. Biological markers such as ER, PR
and HER2 overexpression should be evaluated before treatment. There
might be discordance of these markers between the primary tumor and
the metastatic one, which would lead to dramatic changes in therapy
option. Treatment selection could be made after disease assessment.
1.1.1.5.2 Endocrine therapy of breast cancer
Endocrine therapy was the best choice for hormone receptor-positive
cases because of the fewer side effects compared to chemotherapy.
Tamoxifen, a nonsteriodal estrogen agonist was approved by US Food
and Drug Administration to treat metastatic breast cancer in
postmenopausal females in the 1970s (Robert, 1997). Extensive research
suggested that 5-year tamoxifen treatment was the backbone of
adjuvant hormonal therapy, especially for premenopausal cases
(Jankowitz and Davidson, 2013).
In postomenopausal females, estrogen was predominantly synthesized
from nonglandular sources through aromatase. As a result, aromatase
18
inhibitors were especially important for postomenopausal cases.
Treatment with Letrozole, a nonsteriodal aromatase inhibitor had a
better 5-year overall survival rate compared to tamoxifen treatment
(Tremont et al., 2017). Endocrine therapy has been considered as a
standard choice for ER-positive patients or older patients unfit for
aggressive chemotherapy regimens (Lumachi et al., 2011).
1.1.1.5.3 HER2-targeted therapy of breast cancer
HER2-targeted therapy was an important targeted therapy for first-line
treatment to improve survival of HER2-positive patients. Tyrosine kinase
inhibitor such as lapatinib bound to the intracellular ATP-binding pocket
of the protein kinase domain of HER2. Lapatinib regulated tumor cell
growth by inhibiting the phosphorylation of the cytoplasmic domain of
HER2 (Schramm et al., 2015). Another HER2-targeting drug was
monoclonal antibody such as trastuzumab that interacted with the
extracellular subdomain IV of HER2. Trastuzumab inhibited tumor cell
proliferation and angiogenesis by blocking the ligand-independent HER2
signaling pathway (Schramm et al., 2015).
1.1.1.5.4 Chemotherapy of breast cancer
To patients who were hormone receptor negative or those who were
hormone receptor positive but did not respond to endocrine therapy,
19
chemotherapy was the only remaining choice. Hormone receptor
positive cases could occasionally progress rapidly with metastases. Since
chemotherapy would induce higher response rates than endocrine
therapy, first-line chemotherapy would still be a better choice for
stabilizing this kind of cases before switching to other maintenance
therapy.
Doxorubicin, one of the clinically used anthracyclines, was one of the
most active cytotoxic agents in treating metastatic breast cancer but
inevitably causing cardiotoxicity (Tan et al., 1973).
Paclitaxel was another effective drug for treating breast cancer. It
suppressed breast tumor growth by binding to microtubules and
subsequently stabilizing them by inhibiting depolymerization, which lead
to a mitotic arrest (Schiff et al., 1979). It was approved by the US Food
and Drug Administration for the treatment of metastatic cases which did
not respond to anthracycline-based combination chemotherapy or
relapse in less than six months after adjuvant therapy (Rowinsky and
Donehower, 1995).
The widespread uses of adjuvant systemic therapy such as endocrine
therapy, HER2-targeted therapy and chemotherapy has contributed to a
dramatic reduction in overall mortality rate of breast cancer.
20
1.1.1.6 Breast cancer recurrence
1.1.1.6.1 CSC and breast cancer recurrence
Breast cancer recurrence was a serious problem and was responsible for
the majority of cancer-related deaths (Moody et al., 2005). Recurrence
occurred 5 to 20 years after endocrine treatment. The rate of distant
recurrence was strongly correlated with the TN status when the disease
was first diagnosed (Pan et al., 2017). The mechanism behind breast
cancer recurrence and the possible strategies to stop it remained elusive.
There was a strong correlation between CSC and chemoresistance,
radioresistance and relapse. CSCs were intrinsically resistant to
chemotherapy (Li et al., 2008c). After a 12-week chemotherapy, there
was a great increase in CSC markers (CD44+/CD24-/low) in breast tumor
core biopsies (Chang et al., 2005). Ionizing radiation could also induce
breast CSC properties such as increased mammosphere formation,
tumorigenicity and elevated expression of CSC markers (Lagadec et al.,
2012).
In summary, both chemotherapy and radiotherapy selectively enriched
CSCs, resulting in chemoresistance, radioresistance and metastasis
(Figure 1.6). Targeting CSCs could be a possible way to reduce metastasis
and relapse.
21
Figure 1.6 CSCs lead to breast cancer recurrence
Targeting CSCs together with traditional chemotherapy might reduce metastasis and
relapse. Traditional cytotoxic chemotherapy or radiotherapy could not remove CSCs,
which would lead to cancer relapse or metastasis to distant organs. CSC specific
therapy combined with traditional chemotherapy or radiotherapy might eradicate
cancer. Red cells: CSCs; Grey cells: differentiated cancer cells.
1.1.1.6.2 EMT lead to breast cancer recurrence
Breast cancer recurrence could also be explained by epithelial
mesenchymal transition. The EMT process (Figure 1.4) has been
demonstrated to be involved in antagonizing chemotherapy in breast
cancer.
Slug, as a transcription factor of E-cadherin, also served as a
22
mesenchymal marker of EMT and was found to be transcriptionally
activated in paclitaxel-, docetaxel- and doxorubicin-resistant breast
cancer sublines (Iseri et al., 2011). Immunohistochemistry staining of
breast cancer tissues showed that Snail was highly correlated with breast
cancer resistant protein (BCRP).
Moreover, overexpression of E-cadherin in MCF7 cell line induced BCRP
(Chen et al., 2010). The EMT-inducing transcription factor, zinc finger
E-box binding homeobox 1 (ZEB1) was demonstrated to be a regulator of
radiosensitivity. Radio-resistant breast cancer cells showed upregulation
of ZEB1, which by itself can promote tumor cell radio-resistance both in
vitro and in vivo (Zhang et al., 2014). All these findings indicated that
EMT process was closely associated with chemoresistance and
radioresistance.
There was a direct link between EMT and CSCs. Induction of EMT in
immortalized human mammary epithelial cells would not only lead to
the acquisition of mesenchymal traits but also an increase in CSC
markers and an increase in mammosphere formation. On the other hand,
stem-like cells isolated from breast carcinomas expressed high level of
mesenchymal markers (Mani et al., 2008).
1.1.2 SND1
SND1 (Staphylococcal nuclease domain-containing protein 1) is a
23
multifunctional protein with diverse functions. It regulates gene
expression at both transcriptional and post-transcriptional levels
(Jariwala et al., 2015a). It is a multifunctional protein with numerous
binding partners. In addition, it is a key component of RNA-induced
silencing complex (RISC) with nuclease activity (Gutierrez-Beltran et al.,
2016).
SND1 is found to be overexpressed in breast, prostate, lung, colorectal
and hepatocellular carcinomas and malignant glioma (Jariwala et al.,
2015a; Xing et al., 2018). Apart from its multifunctional role in normal
cells, SND1 also plays different roles in carcinogenesis, making it a very
attractive target for cancer treatment.
1.1.2.1 Identification of SND1
SND1 was initially identified in 1995 as a transcription co-activator by
interacting with transcription activator Epstein-Barr virus nuclear antigen
2 (EBNA2) which was involved in B-lymphocyte transformation. SND1
was found to bind with the acidic domain of EBNA2 (Tong et al., 1995).
1.1.2.2 Structure of SND1
1.1.2.2.1 Secondary structure of SND1
SND1 was evolutionarily conserved. Human SND1 gene was found at
chromosome 7q31.3 (Jariwala et al., 2015b). SND1 sequence contained
24
four similar domains with a 20-33% sequence identity to staphylococcal
nuclease (SN) (Figure 1.7) (Callebaut and Mornon, 1997; Chesneau and
Elsolh, 1994). The fifth domain of SND1 was named as “tudor domain”, a
highly modified nuclease domain originally found in the tudor protein,
which was required during oogenesis for the establishment of a
functional posterior organizing center in Drosophila melanogaster
(Figure 1.7) (Callebaut and Mornon, 1997). Different parts of SND1 had
different functions by interacting with diverse binding partners.
Figure 1.7 Schematic representation of the secondary structure of SND1
SND1 was composed of 5 domains, including 4 tandem repeats of SN domains and a
Tudor-SN5 domain. Different parts of SND1 were identified with different functions.
SN1/2 domain interacted with Metadherin (MTDH). SN3/4 domain showed nuclease
activity. SN1-4 domain had RNA binding activity. Tudor-SN5 domain interacted with
snRNP and Piwi-like protein 1 (PIWIL1).
1.1.2.2.2 Crystal structure of SND1 and its associated-functions
SND1 was an important component of RISC complex (Caudy et al., 2003b;
Yoo et al., 2011c) and its nuclease activity was similar to that of other
25
staphylococcal nuclease because it recognized nucleic acid through the
conserved oligosaccharide-binding-fold domain in its structure (Theobald
et al., 2003).
Tudor-SN5 domain of SND1 interacted with small nuclear
ribonucleoprotien (snRNP), suggesting that SND1 was involved in the
processing of precursor mRNA.
SND1 interacted with PIWIL1 in an arginine methylation-dependent
manner, especially with a preference for symmetrically dimethylated
arginine. The co-crystal structure of tudor-SN5 domain and PIWIL1
peptides (PDB code: 3OMC) revealed an extended Tudor domain of
SND1 accommodating the distinct symmetrically dimethylated arginine
of PIWIL1 through an aromatic cage (Liu et al., 2010).
Besides, the four N-terminal tandem repeats of SND1, especially SN3/4
domain, were required for RNA binding and cleavage. A crystal structure
(PDB code: 3BDL) of SN3, SN4 and Tudor domain of SND1 was solved
revealing a concave basic surface formed by SN3/4 domain, likely to be
involved in RNA binding (Figure 1.8) (Li et al., 2008a).
26
Figure 1.8 Ribbon model of the crystal structure of SN3/4-Tudor-SN5
domains of SND1 (PDB: 3BDL)
The Tudor domain (yellow) was inserted in SN5 (red) and packed between SN4 (green)
and SN5 (red). This figure was adapted from (Li et al., 2008a)
SND1 interacted with MTDH, an important protein involved in many
oncogenic processes (Lee et al., 2013). A co-crystal structure of the
SN1/2 domain of SND1 and an 11-residue MTDH peptide (PDB: 4QMG)
revealed that MTDH peptide occupied an extended groove between SN1
and SN2 domains of SND1 with two tryptophans (W394 and W401)
nestled into two well-defined hydrophobic binding pockets (Figure 1.9).
These two important tryptophans played major roles in MTDH-SND1
interaction and cancer cell survival. In addition, the long protruding arms
and deep surface valleys at the back side of binding interface on SND1,
might be involved in the interactions with other binding partners (Guo et
al., 2014; Wan et al., 2014).
27
Figure 1.9 Co-crystal structure of SN1/2 domain of SND1 with an
11-residue MTDH peptide (PDB: 4QMG)
Green structure represented SN1 domain of SND1; Purple structure represented SN2
domain of SND1; Yellow linear structure represented MTDH 11-residue peptide
(sequence: DWNAPAEEWGN). W394 and W401 in MTDH sequence were very
important amino acids in MTDH binding to SND1. Lβ2-β3 was an essential loop in
MTDH-SND1 binding. This loop was the major difference between SN1/2 domain and
SN3/4 domain, which explained why MTDH interacted with SN1/2 rather than SN3/4
domain of SND1. This figure was adapted from (Guo et al., 2014)
1.1.2.3 Multifunctional roles of SND1
1.1.2.3.1 SND1-mediated regulation of transcription
SND1 as a transcriptional coactivator of EBNA2
28
SND1 was first identified to be p100, a coactivator specifically binding to
the acidic domain of EBNA2. EBNA2 was critical for Epstein-Barr virus in
transforming B-lymphocyte. Overexpression of SND1 in B-lymphocytes
specifically augmented EBNA2 acidic domain-mediated activation. The
co-activating effect was probably mediated by p100 interacting with
TFIIE. (Tong et al., 1995).
SND1 as a transcriptional coactivator of c-Myb
C-Myb was a transcriptional activator involved in the regulation of cell
proliferation, differentiation, and apoptosis. c-Myb was also a regulatory
protein in various types of proliferating cells such as immature
hematopoietic cells (Ness, 1996). c-Myb could interact with SND1, which
could enhance the transcriptional activation of the c-Myb downstream
genes like Pim-1 (Dash et al., 1996). Pim-1 was a serine/threonine
protein kinase and its interaction with SND1 was identified through yeast
two-hybrid screen. SND1-Pim complex functioned as a downstream of
Ras to stimulate c-Myb transcriptional activity in a SND1-dependent
manner (Leverson et al., 1998).
SND1 as a transcriptional coactivator of STAT family
SND1, as a transcriptional coactivator, was also found to interact with a
class of transcription factors: the signal transducer and activator of
transcription (STATs) family (Jariwala et al., 2015a). SND1 could interact
with STAT6, an important mediator of IL-4-regulatory pathway.
29
SND1-STAT6 interaction was mediated by the TAD domain of STAT6 and
the SN-like domain of SND1. SND1 enhanced STAT6-mediated
transcriptional activation and the IL-4-induced Ig epsilon gene
transcription in human B-cell line. In addition, SND1 was found to be
associated with the large subunit of RNA polymerase II and could
mediate the interaction between STAT6 and RNA polymerase II (Yang et
al., 2002).
SND1 could mediate the interaction between STAT6 and CBP, a
co-activator for STAT-mediated gene activation. Chromatin
immunoprecipitation (CHIP) study revealed that SND1 could enhance the
STAT6-SND1-CBP ternary complex formation in the human Ig epsilon
promoter. SND1 was also demonstrated to increase acetylated histone
H4 at the Ig epsilon promoter region (Valineva et al., 2005). Physical
interaction was identified between SND1 and another member of STAT
family STAT5 and their interaction was mediated through both the SN
and the tudor domain of SND1. SND1 also functioned as a transcriptional
coactivator of STAT5 dependent gene regulation (Paukku et al., 2003).
SND1 as a transcriptional coactivator of Smads
Transforming growth factor β (TGFβ) signaling activation was a hallmark
event in the process of cancer metastasis, which regulated the
expression of series of genes involved in tumor invasion and migration.
The TGFβ pathway was mediated by different R-Smads (Smad1, Smad2,
30
Smad3 and Smad5) and Co-Smad (Smad4) transcription factors (Yu et al.,
2017). It was recently demonstrated that SND1 physically interacted with
histone acetylase and recruited it to the promoter regions of Smad2/3/4,
thereby enhancing the gene transcriptional activation of Smad2/3/4.
Smad2/3/4 were critical downstream regulators in the TGFβ1 pathway,
which promoted metastasis of breast cancer (Yu et al., 2017).
1.1.2.3.2 SND1-mediated regulation of post-transcriptional
modification
RNA interference (RNAi) was a process that regulated gene expression
and the final protein synthesis. RISC was the major machinery that
exerted all these functions (Agrawal et al., 2003). SND1 was the first
identified RISC subunit that contained a recognizable nuclease domain,
which contributed to the RNA degradation observed in RNAi in
Caenorhabditis elegans, Drosophila and mammals (Caudy et al., 2003b).
Diverse RISC complexes existed ubiquitously in living organisms but the
central components were similar. A member of the Argonaute proteins
bound to a small interfering RNA (siRNA) and siRNA guided RISC to its
target mRNAs (Figure 1.10) (Pratt and MacRae, 2009).
31
Figure 1.10 The process of RNA interference
Two-stranded RNA was cut by Dicer enzyme, producing siRNAs. Single-stranded
siRNA after its complementary strand degradation would combine with RISC to
specifically decompose mRNA and prevent translation. This figure was adapted from
(Vladimir, 2018).
MTDH, an oncogenic protein found to be overexpressed in different
types of cancers (Shi and Wang, 2015), was also demonstrated to be a
component of RISC. Both MTDH and SND1 were necessary for the
optimal activity of RISC in facilitating siRNA or miRNA-mediated silencing
of genes. MTDH and SND1 overexpression induced RISC activation, which
might contribute to hepatocarcinogenesis (Yoo et al., 2011c).
1.1.2.3.3 SND1 regulated RNA editing
SND1 was a central component of RISC, but it also played an important
32
role in an antagonistic pathway, the degradation of I-dsRNAs and
pre-I-miRNAs in RNA editing process. Long perfect double-stranded RNA
(dsRNA) molecules were important in various cellular pathways. dsRNAs
were extensively modified (hyper-editing) by adenosine deaminases that
acted on RNA, leading to a conversion of 50% adenosine residues to
inosine (I). X. laevis SND1 specifically associated with and promoted
cleavage of model hyper-edited dsRNA substrates, which contained
multiple I·U and U·I pairs (Scadden, 2005). In mammalian cells, SND1
could also degrade pri-miRNA-142 which was edited by ADAR1 and
ADAR2 (Yang et al., 2006).
1.1.2.3.4 SND1 regulated mRNA splicing
Spliceosome, a machinery assembled by small nuclear riboncleoproteins
(snRNP) and associated protein factors, functioned to splice the
precursor mRNA in order to remove introns to produce a mature and
functional mRNA (Will and Luhrmann, 2001). The Tudor domain of SND1
has been shown to interact with snRNPs and Sm proteins, thereby
facilitating spliceosome complex formation and enhancing splicing rate in
vitro (Gutierrez-Beltran et al., 2016; Yang et al., 2007). SND1 might be
involved in alternative splicing in oncogenic processes (David and Manley,
2010).
33
1.1.2.3.5 SND1 as a component of stress granule and its stabilizing
effect of mRNAs
Stress granules (SGs) were composed of non-translating mRNAs,
translation initiation components and many additional proteins affecting
mRNA function. It might affect mRNA translation and stability and might
be linked to nuclear processes and apoptosis (Buchan and Parker, 2009).
SGs also interacted with processing bodies, another cytoplasmic
ribonucleoprotein granule to metabolize cytoplasmic mRNA (Decker and
Parker, 2012).
The interaction of SND1 with core proteins of SGs, such as Pabp1, eIF4E,
eIF5A, TIAR and TIA1 in different organisms, suggested that SND1 was an
essential component of these cytoplasmic foci (Gutierrez-Beltran et al.,
2016). Besides, SND1 might participate in stress-induction by regulating
the aggregation dynamics of poly(A) mRNA-containing SGs selectively
facilitating the stabilization of SG-associated mRNAs during cellular stress
in mammalian cells (Gao et al., 2015). The SND1-dependent stabilization
of specific mRNA might be important for stress adaptation.
1.1.2.4 Role of SND1 in different cancer types
Overexpression of SND1 has been detected in different types of cancers
including liver cancer (Yoo et al., 2011c), breast cancer (Yu et al., 2015a),
colon cancer (Tsuchiya et al., 2007), prostate cancer (Kuruma et al., 2009),
34
lung cancer (Xing et al., 2018) and brain tumor (Tong et al., 2016).
Overexpression and knockdown of SND1 revealed that SND1 participated
in different important process of cancer, such as proliferation, EMT,
angiogenesis, and metastasis.
1.1.2.4.1 Roles of SND1 in breast cancer
SND1 overexpression in breast cancer, especially in metastatic regions
Data from 4 cohorts of breast cancers (containing 818-1105 patient
samples) from The Cancer Genome Atlas (TCGA) indicated that gene
amplification of SND1 was not very significant (0.6-1.5%) in breast cancer.
Mutation and deletion also existed in breast cancer patient samples
(Figure 1.11) (Cerami et al., 2012; Gao et al., 2013). But subsequent
studies revealed a much higher percentage of SND1 overexpression in
protein level in breast cancer (Blanco et al., 2011; Ho et al., 2009a; Yu et
al., 2017; Yu et al., 2015b).
35
Figure 1.11 Breast cancer genomics data of SND1 (TCGA)
Cancer genomics data from cBioportal analyzing data from 4 separate research of the
genomics data of SND1 in invasive breast carcinoma containing 818 (TCGA, Cell 2015),
825 (TCGA, Nature 2012), 1084 (TCGA, PanCancer Atlas) and 1105 (TCGA, Provisional)
patient samples (Cerami et al., 2012; Gao et al., 2013).
SND1 was found to be upregulated in breast cancer tissues, particularly
in primary invasive ductal carcinomas (Yu et al., 2015b). In order to
investigate the relevance of SND1 expression to the invasiveness of
breast cancer, immunohistochemical analysis was performed to detect
SND1 in primary IDC (Invasive ductal carcinoma) and DC (ductal
carcinoma) in situ breast tumor compared with normal tissues. The
expression of SND1 in the IDC samples was significantly higher than that
36
in DC in situ samples. In IDC samples, SND1 expression was positive in all
the 23 studied cases: 78% highly positive and 22% weakly positive (Yu et
al., 2015b).
SND1 overexpression was detected in primary breast cancer. However,
much higher expression of SND1 was detected in long distant metastatic
regions (Yu et al., 2017), which might be the reason of cancer recurrence.
By analyzing tissue microarray data derived from 50 matched cases of
invasive and metastatic lesions, the expression profiles of SND1 were
found to be up-regulated during clinical progression from carcinoma in
situ to invasive and metastatic carcinomas (Ho et al., 2009b).
In another study investigating the relevance of SND1 expression to
breast cancer metastasis, SND1 expression level was detected in primary
breast cancer tissue. SND1-positive breast cancer cells (~80%) in
lymph-node-positive cases were found to be much more than those in
lymph-node-negative cases (~30%) (Yu et al., 2017).
In addition, data reanalysis was conducted on a MSK-82 data set, and the
mean expression of SND1 was found to be significantly higher (p<0.01,
Student’s t test) in patients who developed lung metastases (Figure 1.12)
(Blanco et al., 2011).
37
Figure 1.12 High SND1 expression correlated with increased risk of lung
metastasis of breast cancer
SND1 expression in the primary breast tumor in MSK-82 data set was shown. No Met:
no metastasis; All Met: metastasis to any organ; All LM: lung non-exclusively; LM only:
lung exclusively; All BM: bone non-exclusively; BM only: bone exclusively. This figure
was adapted from (Blanco et al., 2011).
Poor outcomes of breast cancer patients with SND1 overexpression
Survival time was analyzed using clinical data from 23 breast cancer
patients with invasive ductal carcinoma. As shown in Figure 1.13, the
median survival time of patients with high SND1 expression (n=18) was
found to be significantly shorter (57 months) than those with low SND1
expression (n=5, >107 months, p=0.00306) (Yu et al., 2015b).
38
Figure 1.13 Kaplan-Meier survival curves based on SND1 expression in
IDC patients
Median survival time was >107 months (n=5) for SND1 low expression patients and
57 months (n=18) for SND1 high expression patients (P=0.00306). This figure was
adapted from (Yu et al., 2015b).
After analyzing the data from 1133 breast cancer cases (lymph node
positive) with Kaplan-Meier Plotter, patients with high SND1 expression
showed significant reduction in the probability of survival (HR=1.26,
logrank P=0.021) (Figure 1.14).
39
Figure 1.14 Kaplan-Meier survival curves based on SND1 expression in
lymph-node-positive breast cancer patients
A total of 1133 lymph-node-positive breast cancer cases were analyzed with
Kaplan-Meier Plotter. Probability represented the possibility of survival in a given
length of time. SND1 overexpression significantly reduced survival probability of
lymph-node-positive breast cancer patients (Gyorffy et al., 2010).
SND1 promoted metastasis in breast cancer
Breast cancer xenograft mouse model showed that knockdown of SND1
slowed down tumor growth in situ compared with the scrambled control,
indicating SND1 could promote breast cancer tumorigenesis in vivo (Yu
et al., 2015a).
Several Smad-specific recognition domains which were recognized and
40
bound by the Smad complex were identified on the promoter region of
SND1. Under the control of TGFβ1/Smad pathway, SND1 could promote
the expression of E3 ubiquitin ligase Smurf1, leading to RhoA
ubiquitination and degradation. The loss of RhoA subsequently disrupted
F-actin cytoskeletal organization, reduced cell adhesion and promoted
cell migration, invasion and metastasis (Yu et al., 2015b).
The essential role of SND1-MTDH interaction in initiating breast tumor
in transgenic mouse models
The importance of SND1-MTDH interaction was studied by knockout and
add-back experiments (Wan et al., 2014). When SND1-MTDH interaction
was disrupted through mutagenesis of important residues in MTDH,
mammosphere formation in vitro, tumor initiation and tumor growth in
vivo was suppressed (Wan et al., 2014). Under stress conditions, SND1
degradation could be rescued by MTDH-mediated stabilization of SND1
(Wan et al., 2014).
1.1.2.4.2 Roles of SND1 in hepatocellular carcinoma (HCC)
Hepatocellular carcinoma was the most common primary liver
malignancy (Balogh et al., 2016). Liver cancer was the third most
common cause of death from cancer all over the world (WHO, 2018).
SND1 as a multifunctional protein, especially as a metastasis-associated
protein, was found to be overexpressed in ~74% HCC cases compared
41
with normal tissue (Yoo et al., 2011c).
SND1 promoted tumor growth in HCC
Knockdown of SND1 in HCC cell line SMMC-7721 resulted in reduced cell
proliferation, clonal formation and tumor formation in nude mice. SND1
could downregulate IGFBP3, which would explain why SND1 affected
HCC cell proliferation (Yin et al., 2013). In addition, both SND1 and its
binding partner MTDH were upregulated in human HCC cells, which
could be another mechanism explaining hepatocarcinogenesis (Yoo et al.,
2011c).
Moreover, in a very recent study, hepatocyte-specific SND1 transgenic
mice (Alb/SND1 mice) were established and data suggested that these
mice would develop HCC spontaneously with partial penetrance and
exhibit more highly aggressive HCC when chemical carcinogenesis was
included. A relative increase in inflammatory markers and
spheroid-generating tumor-initiating cells (TIC) were observed in the
livers of Alb/SND1 mice, possibly through the Akt and NF-κB signaling
pathways to promote TIC formation in Alb/SND1 mice (Jariwala et al.,
2017).
SND1 promoted angiogenesis in HCC
SND1 also played a role in promoting angiogenesis in liver cancer. SND1
knockdown in liver cancer resulted in a reduction of angiogesis in both
chicken chorioallantoic membrane assay and human umbilical vein
42
endothelial cell differentiation assay. The mechanism was revealed to be
the SND1-induced activation of NF-κB, resulting in the induction of
miR-221 and subsequent induction of angiogenic factors Angiogenin and
CXCL16 (Santhekadur et al., 2012).
SND1 regulated EMT in HCC
Another important event regulated by SND1 in HCC was the EMT process.
By increasing AT1R mRNA stability, SND1 increased angiotensin II type 1
receptor (AT1R) levels, which resulted in an activation of ERK, Smad2 and
the TGFβ signaling pathway. SND1 promoted EMT, migration and
invasion in human HCC cells through this pathway (Santhekadur et al.,
2014).
SND1 regulated cholesterol homeostasis in HCC
SND1 was also found to regulate cholesterol homeostasis in HCC. An
increased cholesterol synthesis was observed in SND1-overexpressing
HCC cells (Navarro-Imaz et al., 2016). Two regulators, SREBP-2 (sterol
regulatory element binding proteins) and SREBP-1 bound to specific sites
in SND1 promoter and regulated SND1 transcription oppositely. SND1
promoter was induced by SREBP-2 activating conditions and repressed
by SREBP-1 overexpression. As a result, a potential contribution of
SREBPs/SND1 pathway to lipid metabolism reprogramming in human
hepatoma cells was proposed (Armengol et al., 2017).
Apart from this, SND1 was also reported to be involved in other lipid
43
metabolism pathways. The interaction between SND1 and a novel
binding partner monoglyceride lipase (MGLL) was recently identified.
SND1 and MGLL interaction resulted in ubiquitination and proteosomal
degradation of MGLL. Overexpression of MGLL in human HCC cells
resulted in a remarkable inhibition of cell proliferation with a significant
delay in cell cycle progression and a remarkable decrease in tumor
growth in nude mice xenograft models, which could be explained by an
inhibition of Akt signaling pathway (Rajasekaran et al., 2016a).
1.1.2.4.3 Roles of SND1 in lung cancer
Lung cancer was the most common cancer for decades and the most
lethal cancer wordwide, causing 1.76 million tumor-related deaths in
2018 (WHO, 2018). Non-small cell lung cancer (NSCLC) was the most
common subtype of lung cancer, accounting for approximately 85% of
lung cancers (Reck and Rabe, 2017).
SND1 induced chemoresistance in lung cancer
SND1, which was overexpressed in NSCLC clinical samples and cell lines,
was found to be very important in maintaining chemoresistance in
NSCLC (Zagryazhskaya et al., 2015). Knockdown of SND1 led to the
increase in the sensitivity of NSCLC to cisplatin, oxaliplatin and
5-fluorouracil, possibly by downregulating S100A11 (S100
calcium-binding protein A11). This would further deregulate the
44
expression of phospholipase A2 in lung cancer (Zagryazhskaya et al.,
2015).
SND1 promoted tumor initiation and progression in lung cancer
A BRAF-SND1 fusion transcript was newly identified in 2015, which
played a potential role in lung cancer development. In an oncogene
fusion transcript screening of 89 lung adenocarcinomas from
non-smokers, a SND1-BRAF fusion transcript formed between exons 1-9
of SND1 and exons 2 to 3’ end of BRAF was detected. After ectopic
expression of SND1-BRAF in H1299 cells, increased levels of MEK/ERK
phosphorylation, cell proliferation, and spheroid formation were
observed (Jang et al., 2015).
SND1 promoted cell migration in lung cancer
A very recent study revealed the role of SND1 in regulating cell migration
in lung cancer. Knockdown of SND1 significantly inhibited lung cancer cell
migration in vitro via miR-320a. Besides, an inverse expression pattern of
SND1 and miR-320a was found in lung cancer tissue and cell lines (Xing
et al., 2018).
1.1.2.5 Current inhibitors of SND1
Deoxythymidine 3’, 5’-bisphosphate (pdTp) was a strong competitive
inhibitor of staphylococcal nuclease (SN) identified after screening a
series of synthetic substrates (Cuatrecasas et al., 1969). Enzymatic
45
reaction between SN and its substrate 4’-p-aminophenylphosphate
5’-phosphate could be inhibited by the competitive inhibitor pdTp
(Cuatrecasas, 1970).
Crystal structure of staphylococcal nuclease-pdTp-Ca2+ complex was
solved to illustrate how this interaction contributed to the inhibition of
the enzymatic activity of SN. Arg-35 and Arg-87 at the active site might
be the dual binding and catalytic residues of this nuclease (Cotton et al.,
1979). Among the four tandem SN domains and the Tudor-SN5 domain,
pdTp showed a highly selective inhibition of SND1 nuclease activity and
the inhibiting concentration is 100µM (Caudy et al., 2003a).
pdTp could inhibit both the proliferation of human liver cancer cell line in
vitro (Yoo et al., 2011c) and tumor growth in human liver cancer
xenografted mice models in vivo (Jariwala et al., 2017).
Immunohistochemical analysis of the tumor sections from the in vivo
mouse model showed a dose-dependent decrease in proliferating cell
nuclear antigen (PCNA), CD133, CD44 and p-p65 staining and an increase
in apoptosis (Jariwala et al., 2017).
1.1.3 MTDH
Metadherin (metastasis adhesion protein or MTDH, also known as
lysine-rich CEACAM1 co-isolated protein (LYRIC) or astrocyte elevated
gene-1 protein (AEG-1)) was an oncogene overexpressed in 44% of
46
breast cancer patients (Li et al., 2008b). It was first identified as an 8q22
genomic gain in breast cancer (Yoo et al., 2011a).
1.1.3.1 MTDH and poor clinical outcomes
Statistical analysis of 225 breast cancer cases revealed a significant
correlation of MTDH status with clinical staging (p=0.001), tumor
classification (p=0.004), node classification (p=0.026), metastasis
classification (p=0.001) and overall survival (Li et al., 2008b). A more
recent meta-analysis comprising 8 studies and covering a total of 1167
breast carcinoma cases, revealed that elevated MTDH would predict
distant and lymph node metastasis in breast cancer (Hou et al., 2016).
1.1.3.2 MTDH structure
Using mouse model injected with cDNAs from lung metastatic breast
carcinoma, Ruoslahti E. and his colleagues successfully identified a
lung-homing domain of MTDH (Figure 1.15) (Brown and Ruoslahti,
2004).
MTDH was highly conserved, encoding for a protein of 582 amino acids
(64kD) in human. MTDH had no conserved functional domains (Britt et
al., 2004; Sutherland et al., 2004). It was a lysine (12.3%) and serine
(11.6%) rich protein with three nuclear localization signals (NLS) and a
single predicted transmembrane domain (TMD) at the N-terminus of the
47
protein, which contained putative dileucine repeats involved in protein
trafficking (Figure 1.15) (Sutherland et al., 2004). Besides, MTDH protein
also contained a C-terminal “GALPTGKS” sequence, which was
postulated to be an ATP/GTP binding site (Thirkettle et al., 2009).
Figure 1.15 A schematic diagram of MTDH protein and its postulated
functional domains
MTDH (378-440) was identified as the lung-homing domain of MTDH in an in vivo
phage display study in mice (Brown and Ruoslahti, 2004). MTDH (393-403) interacted
with SND1. MTDH (435-442) was postulated to be the ATP/GTP binding site. TMD:
transmembrane domain; NLS: nulear localization signal. This figure was adapted from
(Yoo et al., 2011b).
1.1.3.3 MTDH promoted cell proliferation and metastasis of breast
cancer
Biological function of MTDH in breast cancer was investigated extensively.
Ectopic expression or silencing of MTDH in breast cancer cell line MCF7
and MDA-MB-435 significantly enhanced or inhibited cell proliferation
and tumorigenicity, respectively. The proliferation-stimulating effect was
393 403
SND1 interacting motif
ATP/GTP binding site
435 442
48
strongly associated with the down-regulation of the two important
cell-cycle inhibitors p27Kip1 and p21Cip1. Besides, it was demonstrated that
the promotion of proliferation by MTDH was mediated by the regulation
of Akt/FOXO1 signaling pathway (Li et al., 2009).
Knockdown of MTDH in breast cancer cell line LM2, a subline with high
lung metastasis propensity, significantly reduced lung metastasis and
extended mice survival (Hu et al., 2009). Overexpression of MTDH in
breast cancer led to the upregulation of mesenchymal markers and the
downregulation of epithelial markers, resulting in an enhanced invasion
and migration of breast cancer cells (Li et al., 2011).
1.1.3.4 MTDH promoted angiogenesis of breast cancer
Overexpression of MTDH in rat embryo fibroblasts could increase
microvessel formation (Emdad et al., 2009). MTDH overexpression also
increased angiogenesis markers such as angiopointin-1 and tube
formation in matrigel and invasion of human umbilical vein endothelial
cells by upregulating PI3K/Akt signaling pathway (Emdad et al., 2009).
1.1.3.5 MTDH promoted tumor initiation and metastasis in transgenic
mouse model
Functions of MTDH were studied in a MTDH knockout mouse model.
knockout of MTDH significantly inhibited tumor initiation and lung
49
metastasis of mammary tumors in mice (Wan et al., 2014).
Pro-tumorigenic role of MTDH required its binding partner SND1.
Interaction between MTDH and SND1 was required for tumor initiation
and metastasis of mammary tumor in mice. MTDH stabilized SND1,
conferring a survival advantage of mammary cells under stress
conditions. This might explain the crucial role of SND1-MTDH interaction
in mammary tumor formation of mice (Wan et al., 2014).
50
1.2 Objectives
The main purpose of this project was to inhibit breast cancer by
targeting SND1, which was divided into 5 objectives, a) to identify
SND1-interacting peptides through phage display screening; b) to test if
the SND1-interacting peptides could disrupt MTDH-SND1 interaction; c)
to investigate how the disruption of SND1-MTDH interaction resulted in
cytotoxicity in breast cancer; d) to investigate the effect of the disruption
of SND1-MTDH interaction on cell signaling and e) to identify the critical
amino acids in SND1-interacting peptides in cytotoxicity and cell
signaling.
51
Chapter 2 Screening of SND1-interacting
peptides using phage display
2.1 Abstract
SN1/2 domain of SND1 protein was expressed in E.coli and purified with
HisTrap affinity column. Recombinant SN1/2 was used as bait in a phage
display screening. After four rounds of screening, 20 phages were
randomly picked and sequenced. W and Y were found to be highly
enriched after screening. There was a common sequence pattern with 2
W (or one W and one Y) separated by 3-6 amino acids. This pattern was
strikingly similar to what was found in SND1-interacting MTDH peptide
(Guo et al., 2014).
ELISA confirmed that these phages could indeed bind to SN1/2. Six
peptides with highest binding affinity towards SN1/2 were selected for
further studies. Two out of six peptides could disrupt a 22-mer MTDH
peptide from interacting with SN1/2 in ELISA assay. Their relative binding
affinity was determined. Peptide 4-2 and peptide 4-8 could compete
with 22-mer MTDH binding to SN1/2 with an EC50 of 55.4µM and 16.8µM,
respectively. Peptide 4-2 could disrupt SND1-MTDH full-length protein
interaction in co-immunoprecipitation assay. A diagram of the work flow
of this chapter is shown in Figure 2.1.
52
Figure 2.1 Work flow of Chapter 2
a) Phage display was used to identify SN1/2 binders. b) Phage ELISA was performed
to determine the binding affinity of SN1/2 binding phages. c) Peptides selected from
phage display were tested for their ability in disrupting MTDH-SND1 interaction. The
green, purple and yellow structures were the co-crystal structure of SND1-MTDH
(PDB: 4QMG) (Guo et al., 2014). The yellow MTDH peptide is nested in the binding
groove between SN1 (green) and SN2 (purple) domains of SND1.
2.2 Introduction
2.2.1 Phage display technology
Phage display technology could express a library of short peptides at the
end of phages for binding studies. Phage display library was a library of
phage particles that expressed unique sequences of peptides which
would eventually interact with desired protein targets. Ph.D.-12™ Phage
53
Display Peptide Library was a commercially-available combinatorial
library (NEB) of random 12-mer peptides fused to pIII protein coat of
M13 phage. This library consisted of approximately 1X109 different
peptide sequences. Phage display technology was invented by George P.
Smith in 1985 by using filamentous M13 phage (Smith, 1985), which was
an Escherichia coli-specific filamentous bacteriophage with a length of ~1
µm and a diameter of <10 nm.
The phage particle was composed of a single-stranded DNA core inside a
protein coat (Marvin, 1998). The pIII protein was positioned at one end
of the phage capsid and the C-terminus of pIII was composed of three
functional domains (D1, D2 and D3) linked by glycine rich linkers
(Stengele et al., 1990). The D1 and D2 domains were mainly used for
infecting bacteria. They were usually deleted in most of the phage
display systems. The C-terminal D3 domain stayed intact because it was
essential for the assembly of phage capsids and phage production
(Georgieva and Konthur, 2011). Because the C-terminus of phage pIII
coat protein was sometimes modified, peptides were displayed on the
N-terminus of pIII. Instead of displaying only one copy of peptide,
pentavalent peptides could be displayed on the N-terminal fusion of coat
protein pIII (Scott and Smith, 1990).
There were two types of “second-generation” phage display peptide
libraries. One was to construct tailor-made phages using the motif
54
elucidated from a random library, while the other approach was to
establish a “biased random mutagenized library” in which the DNA
sequence of the originally designed peptidomimetic was 10%
“contaminated” by other nucleotides. Using this method, random
variants of the original sequence were created (Freund et al., 2009;
Ophir and Gershoni, 1995).
2.2.2 SND1-MTDH interaction promoted breast cancer
initiation and progression
SND1 interacted with MTDH, an important protein involved in many
oncogenic processes (Lee et al., 2013). MTDH was found to be amplified
in breast cancer and associated with poor prognosis (Wan et al., 2014).
MTDH played an essential role in breast cancer tumorigenesis by
stabilizing SND1 (Wan et al., 2014).
A 22-residue MTDH peptide (386-407) was identified as the minimum
binding motif of MTDH that could interact with SN1/2 domain of SND1.
W394 and W401 were identified as the essential amino acids in
MTDH-SND1 interaction. When SND1-MTDH interaction was disrupted
by mutating the contact residues, mammosphere formation in vitro,
tumor initiation and tumor growth in vivo were suppressed (Wan et al.,
2014).
A co-crystal structure of the SN1/2 domain of SND1 and an 11-residue
55
MTDH peptide (PDB: 4QMG) revealed the details of SND1-MTDH
interaction (Figure 2.2) (Guo et al., 2014). In the co-crystal structure, an
11-residue MTDH peptide occupied an extended groove between SN1
and SN2 domains of SND1 with two tryptophans (W394 and W401)
nestled into two well-defined hydrophobic binding pockets (Figure 2.2).
The long protruding arms and deep surface valleys at the back side of
binding interface on SND1 might also be involved in the interactions with
other binding partners (Guo et al., 2014; Wan et al., 2014).
Figure 2.2 Co-crystal structure of SN1/2 domain of SND1 with an
11-residue MTDH peptide (PDB: 4QMG)
Green structure represented SN1 domain of SND1; Purple structure represented SN2
domain of SND1; Yellow linear structure represented MTDH 11-residue peptide
(sequence: DWNAPAEEWGN). W394 and W401 of MTDH were the 2 critical amino
acids involved in SND1-MTDH interaction. Lβ2-β3 was an essential loop involved in
MTDH-SND1 interaction. This loop was the major difference between SN1/2 and
SN3/4 domain, which explained why MTDH interacted with SN1/2 instead of SN3/4
domain of SND1. This figure was adapted from (Guo et al., 2014).
56
2.2.3 Size exclusion chromatography and multi-angle light
scattering technology
Size exclusion chromatography (SEC), also known as gel permeation, gel
filtration, steric exclusion, or gel chromatography, was an entropically
controlled separation technique which separated particles according to
the relative size or hydrodynamic volume of a macromolecule with
respect to the average pore size of the packing (Barth et al., 1996).
Multi-angle light scattering (MALS) was a technology where light was
scattered into multiple angles when large particles were irradiated by
light to determine both the molecular mass and particle size. In a
SEC-MALS system, the molecular weight of a sample was determined by
MALS after separation by SEC (Sahin and Roberts, 2012).
2.3 Methodology
2.3.1 Expression and Purification of SN1/2
The cDNA encoding full-length SND1 was purchased from DNASU
(https://dnasu.org/DNASU/). The cDNA encoding SN1/2 fragment was
obtained by PCR with 5’
primer-CGGGATCCGTCCCCACCGTGCAGCGGGGCA and 3’
primer-CCGGAATTCTTACTTTTGGTCCAAATTAGCTGTG. SN1/2 cDNA
fragment was cloned into glutathione S-transferase (GST)-6xHis
57
expression vector pET49M.3C and sequenced (Figure 2.3). E.coli BL21
competent cells were transformed with pET49M.3C-SN1/2 plasmid,
cultured in LB medium supplemented with 50µg/mL kanamycin, and
induced with 0.2 mM IPTG at 26°C to express GST-6XHis-SN1/2
recombinant protein.
Figure 2.3 Construction of SN1/2 expression vector
SN1/2 dsDNA was obtained from the cDNA of full-length SND1. It was inserted into
pET49M.3C vector for expression. The multi-cloning sites used were BamHI and
EcoRI.
After induction, bacteria culture was centrifuged and pellet was
ultrasonicated on ice in His binding buffer (15mM β-ME, 1mM PMSF,
20mM sodium phosphate, 40mM imidazole, 0.5M sodium chloride, pH
7.4) followed by centrifugation at 18,000 rpm at 4°C for 90 min. The
58
soluble fraction of lysate was purified by HisTrap column (GE Healthcare
Life Sciences) using AKTA online purifier and eluted with His elution
buffer (20mM sodium phosphate, 500mM imidazole, 0.5M sodium
chloride, pH 7.4).
GST-His-SN1/2 protein was digested with human rhinovirus (HRV) 3C
protease (self-prepared) at 4°C overnight. The digested protein mixtures
(SN1/2 and GST-His tag) was loaded onto HisTrap column and SN1/2
protein was eluted by Tris buffer (50 mM Tris, 150mM NaCl, 10mM KCl
and 10 mM MgCl2, PH8). The fraction containing SN1/2 was analyzed by
SDS-PAGE. The gel was then stained by Coomassie Brilliant Blue.
2.3.2 Screening of a 12-mer phage display library based on
SN1/2
The procedure to screen phage display library was modified according to
the manufacturer’s instructions (NEB, USA). A petri dish (90x15mm) was
coated with SN1/2 before screening. The dish was incubated with
100µg/mL SN1/2 protein at 4°C overnight prior to blocking with 0.1M
NaHCO3 (pH8.6) containing 5mg/mL BSA at 4°C for 1 h. Phage display
library was then added onto the SN1/2-coated petri dish and incubated
at room temperature for 1h. Unbound phages were removed by washing
with TBST (TBS + 0.1% [v/v] Tween-20). Subsequently, bound phages
were eluted with glycine-HCl (pH 2.2) and amplified. Phages with high
59
binding affinity to SN1/2 were harvested after four rounds of biopanning.
Tween-20 was increased to 0.5% [v/v] in TBST washing buffer in round
2-4.
2.3.3 Phage amplification, titering and sequencing
10ml of LB inoculated with ER2738 (an E.coli strain used for M13 phage
infection) was incubated for 4-8h until OD600 reached ~0.5. Infection of
phages to bacteria was accomplished by mixing serial dilutions of phages
with bacteria culture for 3 min under room temperature. Top agar was
then mixed with phage-infected bacteria and poured onto a pre-warmed
LB/IPTG/Xgal plates. Plates were then incubated at 37°C overnight.
For phage titering, plaques on plate were counted (100 plaques per plate
were appropriate). For phage sequencing, single phage clone was picked
from the blue plaque and then inoculated into ER2738 LB culture
(diluting overnight culture of ER2738 at 1:100 into fresh LB.). For phage
amplification, LB was firstly inoculated with ER2738 at 37°C with
vigorous shaking and followed by infection with phages for another 4.5
hours at 37°C. Amplified phages were collected from the supernatant
after centrifugation at 14,000 rpm for 30 seconds. For amplification of
single phage clones, phages could be concentrated by adding 20%
PEG/2.5M NaCl followed by precipitation at 4°C overnight and
resuspended into small volume of TBS.
60
2.3.4 Phage ELISA and peptide ELISA
For phage ELISA, 96-well plate (NuncTM 96-well Optical-Bottom Plate) was
coated with 100µg/mL SN1/2 protein at 4°C overnight prior to blocking
with 0.1M NaHCO3 (pH8.6) containing 5mg/mL BSA at 4°C for 1 h.
Background negative control well was only coated with 0.1M NaHCO3
(pH8.6) containing 5mg/mL BSA at 4°C for 1 h. Serial dilutions of single
phages were added onto the treated plate for interaction studies. One
randomly-picked phage was used as negative control. After incubation at
room temperature for 2 hours with agitation, the plate was washed,
followed by incubating with HRP-conjugated anti-M13 monoclonal
antibody at 0.2µg/mL (Sino Biological, #11973) in blocking buffer at
room temperature for 1h with agitation. The plate was washed before
the addition of HRP substrate ABTS (Thermo Scientific, #34026) in 50mM
sodium citrate, pH4.0. Thirty percent of H2O2 was used as stop solution.
Color product was measured at OD410.
For direct peptide ELISA, 96-well plate (PerkinElmer Optiplate-96F) was
coated with 10µg/mL SN1/2 protein at 4°C overnight prior to blocking
with 0.1M NaHCO3 (pH8.6) containing 5mg/mL BSA at 4°C for 1h (For
BSA coating negative control plate, only BSA was added to block the
plate). Serial dilutions of peptides in binding solution (0.02%TBST) were
added onto the plate. After incubation for 1 hour at 37°C, the plate was
washed with washing buffer (0.02%TBST) before fluorescent signal was
61
detected by CLARIOstar microplate reader (λexcitation=485nm,
λemission=535nm).
For competitive peptide ELISA, the preparation of 96-well plate was the
same as that of direct peptide ELISA. Plates were pre-incubated with
serial dilutions of competitive peptides for 1 h at 30°C, followed by
thorough washing. 22-mer 5-FAM-MTDH peptide (3.5µM) together with
serial dilutions of competitive peptides was added onto the plate for
competition for 1h. The plate was washed before fluorescence detection
by CLARIOstar microplate reader (λexcitation=485nm, λemission=535nm).
2.3.5 SEC-MALS
The protein particles in the purified SN1/2 sample solution were
separated by size exclusion chromatography with a gel filtration column
in Tris buffer (50 mM Tris, 150mM NaCl, 10mM KCl and 10 mM MgCl2,
PH8) and detected by an online multi-angle light scattering detector to
test the aggregation state of SN1/2.
2.3.6 Peptide synthesis
Peptides were synthesized by two peptide companies, Pepmic (Suzhou,
China) and Dechi (Shanghai, China) using standard solid-phase peptide
synthesis chemistry and purified typically to 95% purity as an acetate
form.
62
The six peptide candidates selected from phage ELISA were synthesized
with C-terminus amidation as suggested by Ph.D.-12™ Phage Display
Peptide Library Protocol since these peptides were displayed on the
N-terminus of pIII phage coat protein. Other peptides were synthesized
using the same method in the same purity but with both C-terminus
amidation and N-terminus acetylation for better protection against
enzymatic degradation and stronger cell penetration ability.
5-FAM-MTDH peptide (5-FAM-SSADPNSDWNAPAEEWGNWVDE) and
5-FAM-MTDH scramble peptide (5-FAM-SNWAESWVAPPGEDSADNEWDN)
were synthesized with the same method but with 5-FAM fluorophore
labeled on the N-terminus of the peptides.
2.3.7 Co-immunoprecipitation assay
MDA-MB-231-GFP-
Red-FLuc cell lysate was prepared with modified RIPA lysis buffer (10mM
Tris, 75mM NaCl, 0.5% NP40, pH7.4) supplemented with 1mM PMSF and
1X protease inhibitor (#11836153001,Roche). After centrifugation at
14,000rpm at 4°C for 10 min, supernatant was collected for
co-immunoprecipitation (co-IP) assay. Anti-c-Myc antibody (sc-40) and
anti-V5 antibody (#1905424, Invitrogen) were pre-incubated with protein
G agarose (sc-2002) for 3h before co-IP. Peptide 4-2 was added to the cell
lysate for preincubation at 4°C for 3h. Co-IP was conducted by mixing the
63
treated beads and cell lysate overnight at 4°C with rotation.
2.4 Results
2.4.1 Expression and purification of GST-6XHis-SN1/2
To produce recombinant SN1/2 as bait for phage display screening, a
His-tagged SN1/2 construct was used to produce SN1/2 domain of SND1.
Plasmid map was shown in Figure 2.3. SN1/2 domain of SND1 was
expressed and purified as described in Methodology. Figure 2.4 showed
the chromatogram of purified GST-6XHis-SN1/2 recombinant protein
using HisTrap affinity column. Figure 2.5 showed the SDS-PAGE of the
eluted fractions of GST-6XHis-SN1/2 recombinant protein (indicated by
arrow).
64
Figure 2.4 FPLC purification of GST-6XHis-SN1/2 recombinant protein
Fast Protein Liquid Chromatography (FPLC) was employed to purify GST-6XHis-SN1/2
using HisTrap affinity column. GST-6XHis-SN1/2 and GST-6XHis were the main protein
fractions (indicated by arrows) after expression, which were eluted by gradient
elution. The blue line represented UV absorption, the brown line represented
conductivity and the green line represented salt concentration (gradient) of the
elution buffer. Fraction numbers collected from FPLC were shown on X-axis.
65
Figure 2.5 Purification of GST-6XHis-SN1/2 recombinant protein
Successful expression of GST-6XHis-SN1/2 recombinant protein was reflected by the
presence of a new band corresponding to ~70kD in total lysate. This protein was
soluble, which could be demonstrated by the same band in supernatant.
GST-6XHis-SN1/2 (~70kD) and GST-6XHis tag (~30kD) are the main components
found in fraction 1-9.
After removing the GST-6XHis tag from GST-6XHis-SN1/2 recombinant
protein by HRV 3C protease digestion, SN1/2 domain of SND1 was
purified using the same method. The results are shown in Figures 2.6
and 2.7. The purity of SN1/2 protein was estimated to be ~90% as
indicated by a single band after Coomassie Blue staining (Figure 2.7).
66
Figure 2.6 FPLC purification of SN1/2 protein after HRV 3C protease
digestion
After HRV 3C digestion, GST-6XHis-SN1/2 protein was cleavage into SN1/2 protein
and GST-6XHis tag. The purification of SN1/2 protein was achieved by removing
GST-His tag using Histrap affinity column. The blue line represented UV absorption,
the brown line represented conductivity and the green line represented salt
concentration (gradient) of the elution buffer. Fraction numbers collected from FPLC
were shown on X-axis.
67
Figure 2.7 Purification of SN1/2 protein after HRV 3C digestion
GST-6XHis-SN1/2 was digested by HRV 3C protease. Pure SN1/2 was obtained by
removing GST-6XHis from protein mixture using HisTrap column. Successful cleavage
by HRV 3C protease was indicated by the appearance of SN1/2 (40kD) and GST-6XHis
(30kD) in lane 3 (after digestion). Since GST-6XHis tag interacted with HisTrap column,
SN1/2 was obtained before imidazole gradient elution shown in fraction 2. Bound
GST-6XHis tag was eluted by imidazole elution buffer in fraction 9-12.
2.4.2 SEC-MALS confirmed the monomeric status of SN1/2
SEC-MALS was used to measure the aggregation status of SN1/2 domain
of SND1. As shown in Figure 2.8, a major peak with average molecular
weight ranging from 20kD to 50kD was found. This suggested a
monomeric status of SN1/2 domain of SND1 (estimated molecular
weight 40kD).
68
Figure 2.8 SEC-MALS spectrum confirmed the monomeric status of
purified SN1/2
A major peak of approximately 20-50kD (corresponding to the molecular weight of
SN1/2 of 40kD) was observed in SEC-MALS indicating the monomeric status of SN1/2.
A small fraction of unknown identity was also found.
2.4.3 Phage display screening of peptides binding to SN1/2
The above purified SN1/2 was used as bait in phage display screening. A
12-mer phage display library was used to identify SN1/2 binding phages.
After 4 rounds of biopanning, phages were isolated and peptide
sequences of the phages were determined. As shown in Table 2.1, a total
of 20 phages were picked and sequenced. Sequence of peptide 4-1 is
repeated in 4-18. Sequence of peptide 4-2 is repeated in 4-3, 4-4, 4-7,
4-9 and 4-10. An unusually high percentage of tryptophan was observed
in the peptide sequences. The distance between these tryptophans was
Time (min)
Molar Mass 1 Molar Mass 2 UVM
ola
r Mas
s (g
/mo
l)
69
found to be 3-7 amino acids.
Table 2.1 SN1/2 binding peptides identified from phage display
No. of colonies Peptide sequencing results
4-1 V H W D F R Q W W Q P S
4-2 Q F D Y D H F L M W Y S
4-3 Q F D Y D H F L M W Y S
4-4 Q F D Y D H F L M W Y S
4-5 G H A Y W V D L A S I W
4-6 F H Q P W G Y Y W I S G
4-7 Q F D Y D H F L M W Y S
4-8 W G T I Y Y W E E Y D S
4-9 Q F D Y D H F L M W Y S
4-10 Q F D Y D H F L M W Y S
4-11 D H M P G M K H Y F Y S
4-12 N T H Q Y V G W P I F W
4-13 W Y Y E I D W T S F A L
4-14 S W F S D W D L E L H A
4-15 M W P P S E P R L N Y N
4-16 Y D S R F F L T W W D L
4-17 Y H W H W L D T R D L T
4-18 V H W D F R Q W W Q P S
4-19 W Q W P V R M D W L G S
4-20 H G Y S V W F D S F W L
Twenty SN1/2-binding phages from phage display were picked and sequenced.
Repeated phages (4-1 and 4-18; 4-2, 4-3, 4-4, 4-7, 4-9 and 4-10) were highlighted.
The unusually high percentage of tryptophan (W) was also highlighted.
70
2.4.4 Binding affinity of individual phages to SN1/2
Phage ELISA was performed to determine the binding affinity of the
phages towards SN1/2. As shown in Figure 2.9, the phages interacted
with SN1/2 in a dose-dependent manner. Phages 4-2, 4-5, 4-8, 4-13, 4-16,
4-19 showed high binding affinity towards SN1/2 compared to a
randomly picked control (Figure 2.9a). They were selected for further
study. Phage 4-2, the sequence of which was most repeated after phage
display screening, exhibited medium to high binding affinity among all
the phages.
Other phages showing unexpected or low binding affinity towards SN1/2
were suspended for further assays. Phages 4-6, 4-17 and 4-20 showed
decreased binding at high concentrations for unknown reasons. Phage
4-1, 4-11, 4-12, 4-14, and 4-15 showed low binding affinity towards
SN1/2 compared with the random control (Figure 2.9b).
71
8 10 120
1
2
34-2
4-5
4-8
4-13
4-16
4-19
con-solid
con-dashed
a)
log pfu
SN
1/2
bin
din
g
8 10 120
1
2
3
4-1
4-6
4-11
4-12
4-14
4-15
4-17
4-20
con-solid
con-dashed
b)
log pfu
SN
1/2
bin
din
g
Figure 2.9 Determination of binding affinity of phages towards SN1/2
using ELISA
a) Phage ELISA validated the high SN1/2 binding affinity of the 6 single phage clones
compared to a randomly-picked control. b) Phage ELISA showed decreased binding at
high concentrations or low binding affinity of the phages to SN1/2. The experiments
were conducted in two sets. Con-solid was the control phage used in solid line group.
Con-dashed was the control used in dashed line group. Con-solid and con-dashed
were the same single phage control clone. Phages binding to SN1/2 were recognized
by anti-M13 phage antibody, which also catalyzed ABTS for color detection (OD410).
72
2.4.5 22-mer 5-FAM-MTDH peptide binding to SN1/2
It has been demonstrated that SN1/2 domain of SND1 could interact
with MTDH and SND1-MTDH interaction could induce the initiation and
progression of breast cancer (Wan et al., 2014). Here, such interaction
was studied using a fluorescently-labeled 22-mer 5-FAM-MTDH peptide
(Wan et al., 2014).
As shown in Figure 2.10 a), 5-FAM-MTDH peptide showed a higher
binding affinity towards SN1/2 compared to 5-FAM-MTDH scrambled
control. Neither MTDH nor scrambled control showed any binding
towards BSA. 5-FAM-MTDH scr binding to SN1/2 was subtracted from
5-FAM-MTDH binding to SN1/2 to generate the specific binding of
5-FAM-MTDH to SN1/2 (Figure 2.10 b).
73
0 20 40 60 80 1000
1000
2000
3000
5-FAM-MTDH bindingto SN1/2
5-FAM-MTDH scr binding toto SN1/2
5-FAM-MTDH bindingto BSA
5-FAM-MTDH scr bindingto BSA
Peptide concentration (μM)
Bin
din
g o
f 5-F
AM
-MT
DH
pep
tid
ea)
0 20 40 60 80 1000
500
1000
1500
b)
5-FAM-MTDH peptide con. (μM)
Sp
ecific
bin
din
g o
f
5-F
AM
-MT
DH
to
SN
1/2
Figure 2.10 ELISA study of 5-FAM-MTDH peptide binding to SN1/2
a) ELISA plate was coated with either SN1/2 or BSA. Increasing concentrations of
peptides (5-FAM-MTDH or 5-FAM-MTDH scrambled peptides) were added to the
plate. Fluorescence of 5-FAM was measured after washing. b) 5-FAM-MTDH scr
binding to SN1/2 was subtracted from 5-FAM-MTDH binding to SN1/2 in a) to
generate the specific binding of 5-FAM-MTDH to SN1/2. The mean ±S.D. of
fluorescence is shown (n=3).
74
2.4.6 Peptide candidates competed with MTDH binding to
SN1/2
Here the SN1/2 binding peptides identified from phage display (4-2, 4-5,
4-8, 4-13, 4-16 and 4-19) were investigated for their ability to compete
with 5-FAM-MTDH binding to SN1/2 (Figure 2.12).
Figure 2.11 ELISA study of peptides competed with 5-FAM-MTDH
peptide binding to SN1/2
Peptide 4-2, 4-5, 4-8, 4-13, 4-16 and 4-19 (triangle) competed with 5-FAM-MTDH
peptide binding to SN1/2 coated on the plate. Successful binding of peptides to
SN1/2 would result in lowered 5-FAM-MTDH binding.
As shown in Figure 2.12, peptides 4-2 and 4-8 could compete with
5-FAM-MTDH peptide binding to SN1/2 with EC50s of 55.4µM and
16.8µM, respectively. 4-13 could compete with 5-FAM-MTDH binding to
SN1/2 at low concentrations but unexpectedly enhance this binding at
high concentrations. Unexpectedly, the remaining three peptides: 4-5,
4-16 and 4-19 were found to enhance the binding of MTDH peptide to
SN1/2 for unknown reasons (Figures 2.13 and 2.14).
75
0 100 200 300 4000
1000
2000
3000
40004-8
4-2
4-13
Peptide concentration (μM)
Flu
ore
sc
en
ce
Figure 2.12 Peptide 4-2, 4-8 and 4-13 disrupted 5-FAM-MTDH-SN1/2
interaction
Peptides 4-2 and 4-8 disrupted 5-FAM-MTDH-SN1/2 interaction in a dose-dependent
manner. Peptide 4-13 disrupted 5-FAM-MTDH-SN1/2 interaction only at low
concentrations. The mean ±S.D. of fluorescence is shown (n=3).
0 100 200 300 4000
5000
10000
15000 4-16
4-19
Peptide concentration (μM)
Flu
ore
sc
en
ce
Figure 2.13 Peptide 4-16 and 4-19 enhanced 5-FAM-MTDH-SN1/2
interaction
Disruption study was the same as that in Figure 2.12 but with peptides 4-16 and 4-19.
The mean ±S.D. of fluorescence is shown (n=3).
76
0 100 200 300 4000
50000
100000
150000
200000 4-5
solvent control
Peptide concentration (μM)
Flu
ore
sc
en
ce
Figure 2.14 Peptide 4-5 enhanced 5-FAM-MTDH-SN1/2 interaction
Disruption study was the same as that in Figure 2.12. Peptide 4-5 was dissolved in
DMF-water mixture. The mean ±S.D. of fluorescence is shown (n=3).
2.4.7 Peptide 4-2 disrupted full-length SND1-MTDH complex
Peptide 4-2 was shown to disrupt MTDH-SND1 interaction in ELISA assay,
it would be important to test if peptide 4-2 could also disrupt
SND1-MTDH full-length protein interaction. Since peptide 4-8 could
induce precipitation after fusing with cell penetrating peptide, it was
suspended from this stage.
Here c-Myc-tagged SND1 was overexpressed in
MDA-MB-231-GFP-Red-FLuc cells. Co-Immunoprecipitation experiment
showed that SND1 could pull down MTDH (Figure 2.15 and 2.16)
suggesting that SND1 could interact with MTDH. Peptide 4-2 could
disrupt SND1-MTDH interaction (Figure 2.16).
77
Figure 2.15 co-IP of MTDH by c-Myc-SND1 using c-Myc antibody
Figure 2.16 Disruption of full-length SND1-MTDH complex by peptide
4-2 (c-Myc co-IP)
Co-IP was conducted with c-Myc antibody using cell lysate from
MDA-MB-231-GFP-Red-FLuc-SND1-c-Myc-DDK cells. 30µM of peptide 4-2 could
disrupt SND1-MTDH interaction. Each experiment was conducted for more than 3
times and result from one trial is shown here.
Another approach to test SND1/MTDH interaction was to pull down
MTDH (instead of SND1 as shown above). V5-tagged MTDH was
overexpressed in MDA-MB-231-GFP-Red-FLuc cells. MTDH could pull
down SND1 (Figure 2.17 and 2.18) suggesting that MTDH could interact
78
with SND1. Peptide 4-2 could disrupt SND1-MTDH interaction (Figure
2.18).
Figure 2.17 co-IP of SND1 by V5-MTDH using V5 antibody
Figure 2.18 Disruption of full-length SND1-MTDH complex by peptide
4-2 (V5 co-IP)
Pull-down was conducted with V5 antibody using cell lysate from
MDA-MB-231-GFP-Red-FLuc-MTDH-V5 cells. 30µM of peptide 4-2 could disrupt
SND1-MTDH interaction. The experiment was conducted for more than 3 times and
result from one trial is shown here.
79
2.5 Discussion
2.5.1 Unusually high percentage of tryptophan in SN1/2
binding peptides
After four rounds of screening, 20 single phage clones with strong
binding affinity to SN1/2 were identified. These phages displayed an
unusually higher percentage of tryptophan (Table 2.1). Tryptophan was
rare amino acid in nature (Siemion, 1994). Interestingly, there were two
important tryptophans (W394, W401) in MTDH occupying the groove of
the binding interface of SND1-MTDH complex (Guo et al., 2014) (Figure
2.2). These two tryptophans in MTDH were critical in interacting with
SND1 and promoting tumor initiation (Guo et al., 2014). One could
speculate that the tryptophans found in the SN1/2 binding peptides
might play a similar role with the 2 tryptophans in MTDH in binding to
SND1.
2.5.2 Peptide 4-2 could disrupt SND1-MTDH interaction
Peptide 4-2, which was the most repeated peptide after phage display
screening, showed high binding affinity to SN1/2 in ELISA assay. Peptide
4-2 could also disrupt 22-mer MTDH peptide from interacting with SN1/2
in ELISA assay and could also disrupt SND1-MTDH full-length protein
interaction in co-IP assay, indicating that peptide 4-2 might bind to the
80
binding interface of SND1-MTDH. The sequence of peptide 4-2 had 5
amino acids between one Y and one W, indicating that peptide 4-2 might
be a MTDH-like peptide, which could disrupt SND1-MTDH interaction.
2.5.3 Peptide binding affinity towards SN1/2 (phage ELISA)
corresponded to the ability of disrupting 5-FAM-MTDH-SN1/2
interaction
Phages 4-8 and 4-13 showed a higher binding affinity towards SN1/2
compared to phage 4-2 (Figure 2.9a). Interestingly, peptides 4-8 and 4-13
also competed with 5-FAM-MTDH peptide binding to SN1/2 with lower
EC50s compared to peptide 4-2 (Figure 2.12). This suggested that the
peptides identified from phage display were binding to the interface of
SND1-MTDH interaction.
Peptide 4-5, 4-16 and 4-19 could bind to SN1/2 with high binding affinity
(Figure 2.9a), but they could not disrupt MTDH-SND1 interaction.
Unexpectedly, they could recruit MTDH to bind to SND1 in a dose
dependent manner (Figure 2.13 and 2.14). One possible reason might be
that these peptides could on one hand interact with SN1/2 but on the
other hand also interact with MTDH, forming a sandwich-like structure.
81
2.5.4 5-FAM-MTDH scrambled peptide showed mild binding
affinity towards SN1/2 domain of SND1
5-FAM-MTDH 22-mer scrambled peptide was designed online by a
peptide design tool. Our 5-FAM-MTDH scrambled peptide showed mild
binding affinity towards SN1/2. Two consecutive prolines in the scramble
peptide (SNWAESWVAPPGEDSADNEWDN) might be the reason why this
peptide showed mild binding affinity towards SN1/2. Proline was an
anomalous amino acid whose nitrogen atom was covalently locked
within a ring structure, resulting in a constrained phi angle in this amino
acid (Morgan and Rubenstein, 2013). Consecutive prolines might
facilitate the formation of the secondary structures of proteins or
peptides. The two consecutive prolines in 5-FAM-MTDH scrambled
peptide might form bent structure, which probably resulted in the
strange binding mode of this peptide compared with the fully flexible
linear scrambled peptides. After subtracting MTDH scramble peptide
binding to SN1/2 from MTDH peptide binding to SN1/2, specific binding
of MTDH peptide to SN1/2 was shown.
82
Chapter 3 Cytotoxic effect of CPP-4-2 to
breast cancer cells and its potential
mechanism
3.1 Abstract
CPP-4-2 was constructed by fusing a RR-TAT cell penetrating peptide at
the N-terminus of peptide 4-2 to facilitate its penetration into
mammalian cells. CPP-4-2 preferentially killed breast cancer cell line
MDA-MB-231-GFP-Red-FLuc, MCF7 and MDA-MB-468 compared to
other cancer type SKOV3, A549-Red-FLuc, QGY-7703 or mouse fibroblast
L929. CPP-4-2 killed breast cancer cell by inducing apoptosis. These
results indicated that CPP-4-2 affected a specific survival-associated
pathway in breast cancer cell but not in other cancer types or normal
cell.
Essential amino acids of CPP-4-2 were investigated through mutagenesis.
W and Y were selected for mutagenesis since they were highly enriched
in the peptides after phage display screening. Simultaneous mutation of
Y4, W10 and Y11 to A (producing CPP-4-2AAA) abolished the cytotoxicity
of CPP-4-2 to breast cancer cell. W10A mutation alone abolished the
cytotoxicity, whereas Y4A mutation or Y11A mutation did not. This result
suggested that W10 was essential in the cytotoxicity of CPP-4-2, whereas
Y4 and Y11 were not.
83
The mechanism of CPP-4-2 mediating cytotoxicity in breast cancer cells
was investigated. CPP-4-2 peptide, which could disrupt SND1-MTDH
interaction, could downregulate SND1 in breast cancer cells. The
overexpression of SND1 reduced the cytotoxicity of CPP-4-2 to breast
cancer cells, indicating that CPP-4-2 mediated downregulation of SND1
might be the reason for breast cancer cell death.
For SND1 downstream pathway investigation, CPP-4-2, CPP-4-2Y4A and
CPP-4-2Y11A could affect Akt pathway in breast cancer cells by
upregulating p-Akt S473 and degrading Akt, whereas CPP-4-2AAA and
CPP-4-2W10A could not. The degradation of Akt by CPP-4-2 was
proteasome-dependent and was partially contributed by the
phosphorylation of Akt at S473. Proteomics study indicated that CPP-4-2
affected several important cell survival pathways such as tRNA charging,
protein ubiquitination. Among the differentially expressed proteins, the
transcription of NF-κB2 was confirmed to be significantly enhanced by
CPP-4-2 but not CPP-4-2AAA or CPP-4-2W10A.
The essential amino acid of peptide 4-2 in SND1-interaction was
investigated. Peptide 4-2, 4-2Y4A and 4-2Y11A could disrupt biotinylated
peptide 4-2 interacting with SND1 but 4-2W10A could not. A detailed
molecular docking study revealed that peptide 4-2 interacted with SN1/2
near the binding interface of SND1-MTDH complex.
In summary, peptide 4-2 selectively killed breast cancer cells by inducing
84
apoptosis probably by interacting with SND1, disrupting SND1-MTDH
interaction and inducing SND1 degradation. Peptide 4-2 could also affect
SND1 downstream targets, Akt and NF-κB2 by degrading Akt and
enhancing the transcription of pro-apoptotic NF-κB2, which probably
lead to breast cancer cell death. W10 rather than Y4 or Y11 was the
essential amino acid in the activities of peptide 4-2.
85
3.2 Introduction
SND1 as a multifunctional protein was found to be overexpressed in
many types of cancers. After identifying the SND1 binding peptides, we
were interested in testing their effects on breast cancer cells by fusing
them with a cell penetrating peptide. Multiple pathways were reported
to be the downstream of SND1 including Akt pathway (Rajasekaran et al.,
2016b) and NF-κB signaling (Santhekadur et al., 2012). We were
interested in investigating if SND1 interacting peptide could affect these
pathways, which might lead to breast cancer cell death.
3.2.1 Cell-penetrating peptides
Cell-penetrating peptides (CPPs) were short peptides that could pass
through tissue and cell membrane via energy-dependent or independent
mechanisms. They were widely used to carry a variety of biologically
active conjugates (cargoes) into cells (Guidotti et al., 2017). A number of
peptides with the ability to be internalized into cells were discovered as
shown in Table 3.1. Although there were many ways to classify these CPP
peptides, they were usually classified according to their
physical-chemical properties. All of the newly discovered CPPs fell into
one of the following categories: cationic, amphipathic, or hydrophobic
CPPs (Table 3.1) (Guidotti et al., 2017).
86
Table 3.1 Examples of CPPs and their sequences, origins, and
physical–chemical properties
CPP name Sequence Origin Class
HIV-1 TAT protein,
TAT48−60 GRKKRRQRRRPPQ HIV-1 TAT protein Cationic
HIV-1 TAT protein,
TAT49−57 RKKRRQRRR HIV-1 TAT protein Cationic
Penetratin,
pAntp(43−58) RQIKIWFQNRRMKWKK
Antennapedia Drosophila
melanogaster Cationic
Polyarginines Rn Chemically synthesized Cationic
DPV1047 VKRGLKLRHVRPRVTRMDV Chemically synthesized Cationic
MPG GALFLGFLGAAGSTMGAWSQPKKKRKV HIV glycoprotein 41/SV40 T
antigen NLS Amphipathic
Pep-1 KETWWETWWTEWSQPKKKRKV Tryptophan-rich cluster/SV40 T
antigen NLS Amphipathic
pVEC LLIILRRRIRKQAHAHSK Vascular endothelial cadherin Amphipathic
ARF(1−22) MVRRFLVTLRIRRACGPPRVRV p14ARF protein Amphipathic
BPrPr(1−28) MVKSKIGSWILVLFVAMWSDVGLCKKRP N terminus of unprocessed
bovine prion protein Amphipathic
MAP KLALKLALKALKAALKLA Chemically synthesized Amphipathic
Transportan GWTLNSAGYLLGKINLKALAALAKKIL Chimeric galanin–mastoparan Amphipathic
p28 LSTAADMQGVVTDGMASGLDKDYLKPDD Azurin Amphipathic
VT5 DPKGDPKGVTVTVTVTVTGKGDPKPD Chemically synthesized Amphipathic
Bac 7 (Bac 1−24) RRIRPRPPRLPRPRPRPLPFPRPG Bactenecin family of
antimicrobial peptides Amphipathic
C105Y CSIPPEVKFNKPFVYLI α1-Antitrypsin Hydrophobic
PFVYLI PFVYLI Derived from synthetic C105Y Hydrophobic
Pep-7 SDLWEMMMVSLACQY CHL8 peptide phage clone Hydrophobic
CPPs were classified into three categories: cationic, amphipathic and hydrophobic
CPPs. TAT was the most-studied CPPs and it was selected in this project to direct
peptides into cells. This table was adapted from (Guidotti et al., 2017).
87
The most-studied category of CPP was cationic CPP, which included
TAT-derived peptides, penetratin, polyarginines, and Diatos peptide
vector 1047 (Guidotti et al., 2017). TAT was first identified as CPP in
transcription transactivating protein of HIV-1 (Vives et al., 1997). It was
found that the 15-mer peptide containing the protein transduction
domain of TAT was capable of directing biologically active fusion protein
into all tissues, even into brain (Schwarze et al., 1999).
TAT was the most studied CPP and it showed comparably low cytotoxicity
(El-Andaloussi et al., 2007). Here TAT was fused with peptide 4-2 to
internalize it into cells for functional studies. As the number and the
order of amino acids (especially lycines and arginines) within TAT were
critical in determining the transduction properties (Tuunnemann et al.,
2008; Wender et al., 2000), a hybrid CPP, RR-TAT was also used in this
project to further increase the cell penetrating efficiency and also
increase the solubility of the fused peptide in cell culture medium.
3.2.2 Akt signaling
Akt (also known as protein kinase B, PKB) was reported to be the
downstream of SND1 (Rajasekaran et al., 2016b). It played an
important role in cell metabolism, growth, proliferation, and survival
(Hemmings and Restuccia, 2012). In 1991, the initial identification of Akt
was accomplished by three different groups based on its homology to
88
protein kinase A (Coffer and Woodgett, 1991) and protein kinase C
(Jones et al., 1991) and as the cellular homolog to the retroviral
oncogene viral Akt (Bellacosa et al., 1991). Three isoforms of Akt were
found in mammalian cells, Akt1, Akt2 and Akt3 (Song et al., 2005a).
3.2.2.1 Activation of Akt signaling
The activation of Akt was controlled by a multi-step process involving
phosphoinositide-3-kinase (PI3K) (Hemmings and Restuccia, 2012). PI3K
was a lipid kinase that could generate phosphatidylinositol 3-phosphate
(PIP3), recruiting many downstream proteins to plasma membrane. Class
1A and Class 1B of PI3K involved in the activation of Akt pathway were
activated by tyrosine kinase (RTK) and G-protein-coupled receptors
(GPCR), respectively (Wymann et al., 2003). When these receptors were
activated by ligands, PI3K was first recruited to the plasma membrane,
converting PIP2 to PIP3 (Figure 3.1). Phosphatases such as PTEN could
convert PIP3 back to PIP2 (Hemmings and Restuccia, 2012; Song et al.,
2005b). PIP3 recruited Akt via its lipid-binding PH domain to the plasma
membrane, changing Akt’s conformation and allowing an access of Akt
to phosphoinositide-dependent protein kinase 1 (PDK1) for subsequent
phosphorylation (Song et al., 2005b).
There were two major phosphorylation sites related to the activation of
Akt1, T308 in the activation, or T-loop of the catalytic protein kinase core
89
and S473 in a C-terminal hydrophobic motif (Alessi et al., 1996). The
corresponding residues in Akt2 and Akt3 were located at T309 and S474,
and T305 and S472, respectively (Manning and Toker, 2017). PDK1
phosphorylated AKT1 at T308 site, which was necessary for AKT activity
at a basal level as shown in Figure 3.1 (Alessi et al., 1997). Full activation
of AKT required phosphorylation at S473 in the hydrophobic motif.
Mechanistic target of rapamycin (mTOR) complex 2 (mTORC2) was the
kinase that phosphorylates Akt at S473 for its maximal activation as
shown in Figure 3.1 (Sarbassov et al., 2005). Akt activation could
positively regulate cell survival, cell proliferation, cell metabolism or cell
growth through multiple downstream pathways (Manning and Toker,
2017).
90
Figure 3.1 Molecular mechanisms of Akt regulation
Activation of Akt pathway was a muti-step process. When RTK and GPCR were
activated, PI3K was recruited to the membrane and became activated. PIP2 (PI4,5P2)
was converted into PIP3 (PI4,5P3) under tight regulation of PI3K and PTEN. Akt was
recuited to the membrane by PIP3 and phosporylated by PDK1 at T308, after which
Akt was further phosphorylated by mTORC2 at S473 for full activation. There were
several multi-functional nodes at the downstream of Akt such as FOXO, GSK3 and
TSC2. A number of Akt substrates were also shown at the bottom of this figure. This
diagram was adapted from (Manning and Toker, 2017).
RTK: Tyrosine kinase receptor; GPCR: G-protein-coupled receptors; PIP3:
phosphatidylinositol 3-phosphate; PIP2: phosphatidylinositol 2-phosphate; PDK1:
phosphoinositide-dependent protein kinase 1; mTORC2: mechanistic target of
rapamycin complex 2
91
3.2.2.2 Akt degradation pathways
There were three major protein degradation pathways in mammalian
cells: proteasome, lysosome and autophagosome degradation pathways.
Akt signaling was linked to two important protein degradation systems in
mammalian cells: the ubiquitin–proteasome system and autophagy
system (Noguchi et al., 2014).
There were two types of ubiquitinylation that are associated with Akt:
K48-linked and K63-linked ubiquitinlyation. K48-linked ubiquitinylation
controls proteasomal degradation of Akt and the subsequent
downstream signals, whereas K63-linked polyubiquitination of Akt
served as a regulatory mechanism to promote plasma membrane
recruitment of Akt to facilitate its activation (Mukhopadhyay and
Riezman, 2007; Reyes-Turcu et al., 2009). TT3, BRCA1, and MULAN were
three different proteins found to be involved in the K48-linked
uniquitinylation of Akt.
Tetratricopeptide repeat domain 3 (TTC3) was an E3 ubiquitin ligase,
which interacted preferentially with phosphorylated Akt at T308 to
induce the polyubiquitination and subsequent degradation of AKT in the
nucleus of mammalian cells. It was also reported that overexpression of
wild-type TTC3 could significantly inhibit cell proliferation while on the
other hand, suppression of TTC3 by siRNA could augment cellular
proliferation in HT1080 cells (Suizu et al., 2009).
92
In addition, Akt was demonstrated to directly interact with MULAN, an
E3 ubiquitin ligase which ubiquitinated Akt in vitro and in vivo (Bae et al.,
2012). Phosphorylated Akt was a binding partner and a ubiquitination
substrate of MULAN in the cytoplasm of mammalian cells. Moreover, the
MULAN-induced degradation of Akt could suppress cell proliferation and
viability in HeLa cells (Bae et al., 2012). The discovery of these ubiquitin
ligases or protein factors which could regulate the ubiquitinylation and
the subsequent degradation-related survival suppression suggested a
novel activation-induced suicidal degradation mechanism of Akt (Bae et
al., 2012).
The breast cancer susceptibility gene 1 (BRCA1) was a suppressor gene in
different types of cancers including breast cancer and ovary cancer
(Silver and Livingston, 2012). It was reported that BRCA1 deficiency was
able to activate Akt signaling pathway. Phosphorylation and kinase
activity of Akt were enhanced in BRCA1 mutants. The interaction
between BRCA1-BRCT domains and pAkt S473 would lead to the
ubiquitination of Akt toward protein degradation in the nucleus. BRCA1
mutant cells with BRCT repeats deficiency could accumulate nuclear
pAkt S473 and therefore inactivate the transcription functions of FOXO3a,
a major nuclear target of pAKT (Xiang et al., 2008).
93
3.2.3 NF-κB signaling
NF-κB (nuclear factor-kappaB) was a collective name for inducible
dimeric transcription factors which was composed of Rel family of
DNA-binding proteins (Karin and Ben-Neriah, 2000). It was an essential
gene involved in the activation of large numbers of genes responding to
infection, inflammation and cell survival (Karin and Ben-Neriah, 2000).
NF-κB family contained 5 members of transcription factors,
NF-κB1/p105/p50, NF-κB2/p100/p52, RelA/p65, RelB and c-Rel. They
could form heterodimers or homodimers and subsequently bound to
consensus DNA sequences at promoter regions of responsive genes (Xia
et al., 2014). Under normal condition, NF-κB was localized in the
cytoplasm of non-stimulated cells but when NF-κB pathway was
activated, it was translocated into the nucleus for transcriptional
activation of downstream genes (Karin and Ben-Neriah, 2000). The
activation of NF-κB through molecular translocation was controlled by
the phosphorylation and subsequent degradation of inhibitors of kappa
B (IκB) (Baldwin, 1996).
NF-κB played a very important role in cancer initiation, development,
metastasis and chemo-resistance (Xia et al., 2014). NF-κB was known to
promote cell survival by upregulating many anti-apoptotic genes, such as
Bcl-2 homologues A1/Bfl-1 and Bcl-xL, IEX-1 and XIAP (Baldwin, 2001).
Interestingly, NF-κB also showed pro-apoptotic activity depending on the
94
stimulus given (Kaltschmidt et al., 2000).
NF-κB2/p100
NF-κB2 was the most frequently mutated NF-κB member in human
lymphoma (Rayet and Gelinas, 1999). NF-κB2/p100 could undergo
proteolytic cleavage to generate a 52k polypeptide (p52) which
corresponded to the N-terminal half of p100 (Xiao et al., 2001). P100
protein was composed of Rel homology domain, ankyrin repeats and
death domain, whereas P52 was only composed of Rel homology
domain after proteolytic processing (Figure 3.2) (Xiao et al., 2001). The
C-terminal ankyrin repeats contained intrinsic IκB activity (Senftleben et
al., 2001). The Rel homology domain was required for dimerization, DNA
binding, interaction with IκBs, and nuclear translocation (Oeckinghaus
and Ghosh, 2009).
Figure 3.2 Secondary structures of p100 and p52
NF-κB2/p100 was consisted of Rel homology domain, Ankyrin repeats and Death
domain. NF-κB2/P52 contained only Rel homology domain (Xiao et al., 2001). The Rel
homology domain was responsible for dimerization, DNA binding, interaction with
IκBs, and nuclear translocation (Oeckinghaus and Ghosh, 2009).
95
The death domain of p100 might play a pro-apoptotic function in cancer
cells. A selective activation of p52 was detected in human breast cancer
tissue (Cogswell et al., 2000). Moreover, C-terminal deletions of NF-κB2
gene and subsequent generation of p100 mutants without the death
domain were found in human lymphoid tumors (Rayet and Gelinas,
1999). This information indirectly suggested p100 played a pro-apoptotic
function, which was opposite to the commonly known anti-apoptotic
function of p52 in cancer cells.
The pro-apoptotic function of p100 and anti-apoptotic function of p52
were further investigated. The death domain at the C-terminus of p100
was found to be absent from all known tumor-derived mutants. It was
found to inhibit cell growth and was essential for the pro-apoptotic
activity of p100. It could also mediate the recruitment of p100 into death
machinery complexes after ligand stimulation. Interestingly, colony
formation assay of mouse fibroblast with activated Ras suggested p100
and p52 had anti- and pro-oncogenic activities, respectively. Caspase-8
was revealed to be essential in mediating the anti-oncogenic function of
p100 (Wang et al., 2002).
Myc oncoproteins were found to be activated in approximately 70% of
human malignancies (Boxer and Dang, 2001). It was reported to
transactivate genes through binding to consensus ‘-CACGTG-3’ or E box.
It could also suppress transcription by inhibiting gene initiator (Dang,
96
1999). The NF-κB pathway was found to be suppressed in Myc-driven
human Burkitt lymphoma (Dave et al., 2006). Myc oncoprotein could
suppress the transcription of NF-κB2. The loss of NF-κB2 was able to
accelerate Myc-induced lymphomagenesis by impairing apoptosis in
Eμ-Myc transgenic mice (Keller et al., 2010).
3.3 Methodology
3.3.1 Cell seeding, peptide treatment and MTS assay
A total of 5000-8000 cells were seeded per well into a 96-well tissue
culture plate for attachment for 24h in RPMI medium, after which
peptides were diluted into series dilutions and added onto cells for
incubation. After 72h, medium was removed followed by the addition of
MTS, PMS, and medium solution (prepared according to the instruction
of Promega). Cells were then incubated for another 1h at 37°C before
OD490 was measured by a micro-plate reader.
3.3.2 Cell culture, peptide treatment and cell transfection
MDA-MB-231-GFP-Red-FLuc, MCF7, MDA-MB-468, L929, QGY-7703,
A549-Red-FLuc and SKOV3 cell lines were cultured in RPMI Medium 1640
(gibco) supplemented with antibiotics P/S (100U/mL penicillin,
100µg/mL Streptomycin) and 10% fetal bovine serum (FBS, HyClone) at
37°C with 5% CO2. Subculture was performed when the cell density
97
reached approximately 80-90% confluent.
For testing the effect of CPP-4-2 on Akt pathway,
MDA-MB-231-GFP-Red-FLuc cells were seeded and grown to 80-90%
confluent before peptide treatment. Cells were incubated with CPP-4-2
and its mutant peptides for 24h before lysis for western blot analysis.
Stable transfection of MDA-MB-231-GFP-Red-FLuc cell line with
pCMV6-Entry-SND1-cMyc-DDK plasmid (#RC200059, Origene) and
pLX304-MTDH-V5 plasmid (HsCD00438838, DNASU) (Figure 3.3) was
conducted using lipofectamine 3000 reagent (Thermo Fisher) according
to the manufacturer’s instruction. After transfection,
MDA-MB-231-GFP-Red-FLuc cells were selected with G418 at the
concentration of 2mg/mL or blasticidin at the concentration of 10µg/mL
for 2 weeks.
Figure 3.3 Maps of pCMV6-Entry-SND1-cMyc-DDK plasmid and
pLX304-MTDH-V5 plasmid
pCMV6-Entry-SND1-cMyc-DDK plasmid and pLX304-MTDH-V5 plasmid were used in
the construction of MDA-MB-231-GFP-Red-FLuc transgenic cell lines.
98
3.3.3 Biotinylated 4-2 peptide pull-down assay
MDA-MB-231-GFP-Red-FLuc and SKOV3 cell lysate was prepared with
modified RIPA lysis buffer (10mM Tris, 75mM NaCl, 0.5% NP40, pH7.4)
supplemented with 1mM PMSF and 1X protease inhibitor
(#11836153001,Roche). After centrifugation at 14,000rpm at 4°C for 10
min, supernatant was collected for pull down assay. For peptide
pull-down assay, 20 nmoles of biotinylated 4-2 peptide was
pre-incubated with streptavidin agarose breads (Thermo Fisher) for 3h
before IP. For pull-down assay with competitive peptides, 40 nmoles of
4-2 and its mutant peptides were added to cell lysate for preincubation
at 4°C for 3h. Pull down assay were conducted by mixing the treated
beads and cell lysate overnight at 4°C with rotation.
3.3.4 Peptide synthesis
Peptides used here were synthesized using the same method as
described in Chapter 2. Biotinylated 4-2 peptide was synthesized with
biotinylation at the N-terminus of peptide 4-2.
3.3.5 Western blot
Protein samples with SDS loading dye were loaded onto 10%
polyacrylamide gel for separation and then transferred to a PVDF
Immobilon P membrane (MilliPore). The membrane was blocked by
99
incubation in TBST (10mM Tris-HCl; pH 7.6, 150mM NaCl, 0.05%
Tween20) containing 5% non-fat milk at room temperature for 1 hour
with agitation. After blocking, the membrane was washed 3 times with
TBST, each for 5 minutes with agitation, and then incubated with
1:1000-3000 primary antibody, anti-MTDH antibody (#40-6500,
Invitrogen), anti-SND1 antibody (sc-271590), anti-β-actin antibody
(sc-47778), anti-p-Akt S473 antibody (#9271, Cell Signailing) and anti-Akt
antibody (#4691, Cell Signailing) in TBST overnight at 4°C with agitation.
The membrane was then thoroughly washed as mentioned above,
followed by incubation with 1:3000 secondary antibody, goat anti-rabbit
or rabbit anti-mouse IgG-HRP (Santa Cruz Biotechnology Inc.) in TBST for
1 hour at room temperature with agitation. After washing with TBST, the
membrane was incubated with the SuperSignal Substrate Western Blot
kit (Pierce) before chemiluminescence signal detection by the Azure
C600 western blot imaging system.
3.3.6 In silico docking of peptide 4-2 to SN1/2
3.3.6.1 Determination of the binding pockets on SN1/2
ICMPocketFinder Tool (PMID: 15757999) identified potential pockets in
SN1/2 (PDB: 4QMG) using ICM-Pro (Miller et al., 2011). Five tentative
pockets were chosen for further study. For each pocket, a box space
region was drawn around it. Two more boxes were defined, one (Boxi)
100
around the interface of MTDH peptide and SN1/2 and the other one
(Boxno) as a big box containing the whole structure of SN1/2.
3.3.6.2 Peptide sampling using Monte Carlo method
The 7 boxes mentioned above were used to fit peptide 4-2. Peptide 4-2
was sampled in the potential map ensembles through biased probability
Monte Carlo method with W10 restrained to each of the 7 boxes to
optimize peptide 4-2 (W10 has been proved to be the essential amino
acid in interacting with SN1/2). After the presampling of peptide 4-2, 16
top conformations were saved as starting conformations for next step
peptide docking. Each starting conformation was further flipped to
generate 4 principal starting poses, which were sampled through biased
probability Monte Carlo method to optimize the positional and internal
variables with W10 (in peptide 4-2) restrained in the tentative binding
site.
After docking, 50 top ranking conformations were saved for each starting
pose for further analysis. Docking score ≤-190 was chosen as a criterion
to select the conformations of the highest possibility to bind to SN1/2.
3.3.7 Proteomics analysis
MDA-MB-231 cells were cultured as described above. Cells were
harvested and lysed in cell lysis buffer (10mM Tris pH 7.4, 75mM NaCl,
101
0.1%SDS). Soluble proteins were collected in the supernatant of cell
lysate after centrifugation at 12,000g for 10min. Protein concentration
was determined by Bradford (Bio-Rad).
100µg of soluble proteins of each samples were digested with trypsin
and then analyzed by mass spectrometry. The digested peptide mixture
was analyzed by Bruker amaZon speed ESI-ion trap-ETD mass
spectrometer (Thermo Fisher Scientific) coupled with LC-MS/MS by an
EASY-nLC system (Thermo Fisher Scientific) through a nanoelectrospray
ion source. Samples were concentrated and desalted online with a
pre-column (2cm; 100μm ID; 5μm C18-A1; Thermo). Separation was
conducted using Acclaim PepMap 100 C18 column (10cm; 75µm ID; 3µm
C18-A2; Thermo). A linear gradient of A and B buffers (buffer A: A = 0.1%
formic acid; Buffer B = 99% ACN, 0.1% formic acid) from 1% to 50%
buffer B for a total of 77 min at a flow rate of 0.3 μL/min was used to
elute peptides into the mass spectrometer. Mass spectra were obtained
in the positive-ion mode over the range m/z 400-1500. Proteins were
identified by identifying at least 3 unique peptides in one protein.
Pathway analysis of the differentially expressed proteins was performed
by IPA (Ingenuity Pathway Analysis, QIAGEN).
3.3.8 RNA extraction and Real-time PCR
mRNA was extracted from cell pellets using the Trizol Reagent (Life
102
Technologies). cDNA synthesis was performed by incubating with 2µg
RNA with RT Buffer, dNTP, RT random primers and Reverse Transcriptase
using High Capacity cDNA Reverse Transcription Kit (Thermo Fisher
Scientific) at 25 °C for 10min, 37°C for 120min followed by 85°C for 5min.
cDNA (0.5µL RT reaction buffer) was amplified in 10µL real-time PCR
buffer containing 4pmol of each primer and 5µL SsoFast EvaGreen
Supermix with Low ROX (BIO-RAD). Primers used were listed as follows,
ITGB4 primers: 5'-GCAGCCCCATCTCCTAGC-3', 5'-ATCCTCTTCCTCCCTCTCC
C-3'; EP400 primers: 5'-ACAGTGAGGACGCAGTGATG-3',
5'-CATCCTCTCGCGTGTAGGTC-3'; NF-κB2 primers:
5'-TGGCCGGGACAAGAGAAAAG-3', 5'-CATCCAGACCTGGGTTGTAGC-3';
NF-κB1 primers: 5'-CCAACAGATGGCCCATACCT-3',
5'-AACCTTTGCTGGTCCCACAT-3'; BCL2 primers:
5'-CAGGATAACGGAGGCTGGGATG-3', 5'-GACTTCACTTGTGGCCCAGAT-3';
Bax primers: 5'-AAACTGGTGCTCAAGGCCC-3',
5'-AAAGTAGGAGAGGAGGCCGT-3'; β-actin primers:
5’-CTCTTCCAGCCTTCCTTCCT-3', 5’-AGCACTGTGTTGGCGTACAG-3’.
Real-time PCR was performed with 1 cycle at 95°C for 30s, 35 cycles at
95°C for 10s and 60°C for 30s, and 81 cycles at 55°C for 30s.
3.3.9 5-FAM-CPP-4-2 accumulation assay and flow cytometry
Different cell lines were detached and washed with PBS before
103
incubating with 10µM 5-FAM-CPP-4-2
(5-FAM-YGRKKRRQRRRQFDYDHFLMWYS-NH2) in 37°C for 2h in RPMI
medium with shaking. Cells were then washed with PBS and suspended
in FACS flow cytometry buffer (1% BSA, 1mM EDTA in PBS). Peptide
accumulation in different cell lines was detected with BD FACSVia cell
analyzer.
3.3.10 Apoptosis assay and Flow cytometry
MDA-MB-231-GFP-Red-FLuc cells were seeded for 3 days to 70-80%
confluence, followed by incubation with peptides for 24h before
detachment. Annexin V and PI staining (#556419, BD Pharmingen) was
performed according to the instructions of manufacturer. Annexin V and
PI signals was detected with BD FACSVia cell analyzer.
104
3.4 Results
3.4.1 CPP-4-2 preferentially killed breast cancer cells
CPP-4-2 was constructed by fusing RR-TAT, a hybrid CPP at the
N-terminus of peptide 4-2 to facilitate the penetration of peptide 4-2
into mammalian cells. Another SND1 interacting peptide 4-8 was found
to precipitate significantly in tissue culture media after fusing with CPP
so it was suspended. As shown in Figure 3.4, CPP-4-2 exhibited
preferential cytotoxicity towards breast cancer cell lines
MDA-MB-231-GFP-Red-FLuc, MCF7 and MDA-MB-468 with an IC50 of
22.4±1.0µM, 18.7±0.2µM and 15.9±6.2µM, respectively (Table 3.2). On
the other hand, CPP-4-2 was much less toxic to other cancer types
including SKOV3, QGY-7703, A549-Red-FLuc, and L929 (mouse SND1 was
highly similar to human SND1 with only several difference of residues)
under the same condition.
Different killing effects of CPP-4-2 towards different cell lines might be
due to different cell penetrating efficiency. CPP-4-2 accumulation in
different cell line was tested by flow cytometry. Comparable amount of
5-FAM-CPP-4-2 was detected in all the cell lines except MDA-MB-468,
which accumulated 2-3 folds of CPP-4-2 (Figure 3.5). To summarize,
CPP-4-2 preferentially killed breast cancer but not other cancer types or
normal cell. The mechanism of the cytotoxicity of CPP-4-2 was tissue
specific.
105
0 10 20 30 40 500.0
0.5
1.0
1.5
MDA-MB-231-GFP-Red-FLuc
MCF7
MDA-MB-468
QGY-7703
A549-Red-FLuc
SKOV3
L929
CPP-4-2 con. μM
OD
490
Figure 3.4 CPP-4-2 preferentially killed breast cancer cell lines
Different cell lines were incubated with serial dilutions of CPP-4-2 in RPMI medium
for 72h before MTS assay. The mean ±S.D. of OD is shown (n=3).
Table 3.2 IC50s of CPP-4-2 of different cell lines
Cell line Cancer type IC50 (µM, n≥3)
QGY-7703 Hela derivative >40
A549-Red-FLuc Lung >40
L929 Fibroblast (mouse) >40
SKOV3 Ovarian 32.4±6.7
MDA-MB-231-GFP-Red-FLuc Breast 22.4±1.0
MCF7 Breast 18.7±0.2
MDA-MB-468 Breast 15.9±6.2
IC50s of CPP-4-2 of different cell lines were calculated according to the data from
Figure 3.4.
106
A54
9
QGY-7
703
L929
SKOV3
MDA-M
B-2
31
MCF7
MDA-M
B-4
68
0
50000
100000
150000
200000A549
QGY-7703
L929
SKOV3
MDA-MB-231
MCF7
MDA-MB-468
Ab
so
lute
flu
ore
scen
ce
Figure 3.5 CPP-4-2 accumulated equally among different cell lines
Different cell lines were incubated with 10µM of 5-FAM-CPP-4-2 for 2h before flow
cytometry analysis. Absolute fluorescence was obtained by subtracting untreated
control from peptide treatment group. The mean ±S.D. of absolute fluorescence of
5-FAM-CPP-4-2 is shown (n=2).
Since CPP-4-2 showed preferential cytotoxicity towards breast cancer cell
lines, the expression of SND1 in different cell lines were investigated.
Endogenous expression of SND1 in different cell lines was shown in
Figure 3.6. The cytotoxicity of CPP-4-2 towards different cell lines was
irrelevant to the endogenous level of SND1.
107
Figure 3.6 Expression level of SND1 in different cell lines
Expression of endogenous SND1 in different cell lines was shown. SND1 expression
was normalized to β-actin. Western blot experiment was conducted for more than 3
times and result from one trial is shown in a).
3.4.2 Investigation of the essential amino acids of CPP-4-2 in
cytotoxicity
Essential amino acids of CPP-4-2 in its cytotoxicity were investigated. Y
and W were selected for mutagenesis since they were highly enriched
after phage display screening. A series of mutants of CPP-4-2 (Table 3.3)
were synthesized. Figure 3.7 showed that cell penetrating peptide CPP
was not toxic to breast cancer cell. CPP-4-2 was highly toxic to
MDA-MB-231-GFP-Red-FLuc cell line with an IC50 of 23.6±2.5µM
compared to CPP-4-2AAA and CPP-4-2W10A (IC50>40µM, Table 3.3).
CPP-4-2Y4A and CPP-4-2Y11A were equally toxic as CPP-4-2 with IC50s of
23.9±2.5 and 22.2±1.6µM, respectively (Table 3.3). This result suggested
that W10 was the essential amino acid in CPP-4-2 in its cytotoxicity to
108
MDA-MB-231-GFP-Red-FLuc cells while Y4 and Y11 were not.
Table 3.3 Cytotoxicity of CPP-4-2 and its mutants on
MDA-MB-231-GFP-Red-FLuc cells
Peptide Name Sequence IC50 (µM, n≥3)
CPP RRRKKRRQRRR >40
CPP-4-2 RRRKKRRQRRRQFDYDHFLMWYS 23.6±2.5
CPP-4-2Y4A RRRKKRRQRRRQFDADHFLMWYS 23.9±2.5
CPP-4-2W10A RRRKKRRQRRRQFDYDHFLMAYS >40
CPP-4-2Y11A RRRKKRRQRRRQFDYDHFLMWAS 22.2±1.6
CPP-4-2AAA RRRKKRRQRRRQFDADHFLMAAS >40
The suspected essential amino acids in CPP-4-2 peptide were mutated into alanine
(labeled in red). IC50s of these peptides to MDA-MB-231-GFP-Red-FLuc cells were
calculated according to the data from Figure 3.7.
0 10 20 30 40 500.0
0.5
1.0
1.5
CPP-4-2
CPP-4-2Y4A
CPP-4-2W10A
CPP-4-2Y11A
CPP-4-2AAA
***
***
CPP
con. μM
Perc
en
tag
e s
urv
ival
Figure 3.7 Cytotoxicity of CPP-4-2 and its mutants on
MDA-MB-231-GFP-Red-FLuc cells
MDA-MB-231-GFP-Red-FLuc cells were incubated with serial dilutions of CPP-4-2 in
RPMI medium for 72h before MTS assay. The mean ±S.D. of OD is shown (n=3).
109
3.4.3 CPP-4-2 killed breast cancer cells by inducing apoptosis
Since CPP-4-2 could kill breast cancer cell MDA-MB-231-GFP-Red-FLuc,
we wanted to investigate if the cytotoxicity of CPP-4-2 to breast cancer
cells was due to CPP-4-2 mediated apoptosis. Figure 3.8 showed that
CPP-4-2 could induce early (34.1%) and late apoptosis (12.4%) on
MDA-MB-231-GFP-Red-FLuc cells when compared to CPP-4-2AAA (20.4%
early apoptosis, 0.4% late apoptosis) and untreated control (13.2% early
apoptosis, 0.0% late apoptosis). This result suggested that CPP-4-2 killed
breast cancer cell MDA-MB-231-GFP-Red-FLuc by inducing apoptosis.
Figure 3.8 CPP-4-2 induces apoptosis of breast cancer cells
MDA-MB-231-GFP-Red-FLuc cells were treated with 30µM of peptides in
RPMI medium for 4h before Annexin V and PI staining followed by flow
cytometry analysis. Peptide treatment and flow cytometry analysis were
conducted for more than 2 times and result from one trial is shown.
110
3.4.4 Biotinylated 4-2 peptide pulled down full-length SND1
In order to prove the interaction of peptide 4-2 and SND1, a biotinylated
4-2 peptide was synthesized and used to pull down SND1 from cell lysate.
It was found that biotinylated 4-2 peptide could pull down SND1 from
MDA-MB-231-GFP-Red-FLuc cells (Figure 3.9 and 3.10). Excess unlabeled
4-2 peptide could successfully compete for the pull down, demonstrating
the specificity. Interestingly, biotinylated 4-2 peptide could not pull down
SND1 from SKOV3 cell lysate, probably due to the low endogenous
expression level of SND1 in such cell line.
Figure 3.9 Biotinylated 4-2 peptide pulled down SND1 (diagram)
SND1 was pulled down by biotinylated 4-2 peptide using streptavidin agarose beads.
111
Figure 3.10 Biotinylated 4-2 peptide pulled down SND1
Pull down assay was conducted with cell lysate from MDA-MB-231-GFP-Red-FLuc or
SKOV3 cells using biotinylated 4-2 peptide (20µM). SKOV3 expressed relatively low
level of SND1 compared with MDA-MB-231-GFP-Red-FLuc. PTEN and β-actin were
used as unrelated negative controls. Excess peptide 4-2 (40µM) was used in
competition assay. The experiment was conducted for more than 3 times and result
from one trial is shown here.
3.4.5 Investigation of the essential amino acids of peptide 4-2
in SND1 interaction
To investigate the essential amino acids of peptide 4-2 in SND1
interaction, a series of mutants of peptide 4-2 were synthesized as
shown in Table 3.4. These peptides showed different cytotoxic effect
towards MDA-MB-231-GFP-Red-FLuc cells as investigated before (Figure
3.7).
112
Table 3.4 Sequences and cytotoxicity of peptide 4-2 and its mutants
Peptide Name Sequences Cytotoxicity to
MDA-MB-231-GFP-Red-FLuc
4-2 QFDYDHFLMWYS +
4-2Y4A QFDADHFLMWYS +
4-2W10A QFDYDHFLMAYS -
4-2Y11A QFDYDHFLMWAS +
Hydrophobic amino acids (W and Y) of peptide 4-2 were mutated into alanine
(labeled in red). The cytotoxic effect of these peptides towards
MDA-MB-231-GFP-Red-FLuc cells (Figure 3.7) was shown in the last column.
Pull down assays of SND1 by biotinylated 4-2 peptide was conducted in
the presence of competing peptides (Figure 3.11). Figure 3.12 showed
that 4-2, 4-2Y4A and 4-2Y11A could compete with the pull-down of
SND1 by biotinylated 4-2 whereas 4-2W10A could not. This result
suggested that W10 was an essential amino acid of peptide 4-2 in
interacting with SND1 whereas Y4 or Y11 were not. The ability of the
peptides to interact with SND1 was consistent with the cytotoxicity of
these peptide (Table 3.5), suggesting that the cytotoxicity of the peptides
was dependent on their interaction with SND1.
113
Figure 3.11 4-2 and its mutant peptides competed with the pull down
of SND1 by biotinylated 4-2 peptide (diagram)
SND1 was pulled down by biotinylated 4-2 peptide using streptavidin agarose beads.
Biotinylated 4-2 peptide pulled down SND1 in the presence of competing peptide 4-2
(a) or non-competing peptide 4-2 mutant (b).
Figure 3.12 W10 was the essential amino acid in SND1-interaction
Pull-down assay was conducted using biotinylated 4-2 peptide and cell lysate from
MDA-MB-231-GFP-Red-FLu with or without competing peptides. 4-2, 4-2Y4A and
4-2Y11A (80µM) could compete with the pulling down of SND1 by biotinylated 4-2
(40µM) while 4-2W10A (80µM) could not. β-actin was used as unrelated negative
control; The experiment was conducted for more than 3 times and result from one
trial is shown here.
114
Table 3.5 Cytotoxicity and SND1 binding ability of peptide 4-2 and its
mutants
Peptide Name Cytotoxicity to
MDA-MB-231-GFP-Red-FLuc
SND1 interaction
4-2 + +
4-2Y4A + +
4-2W10A - -
4-2Y11A + +
Cytotoxicity of the peptides towards MDA-MB-231-GFP-Red-FLuc cells and their
ability to interact with SND1 in MDA-MB-231-GFP-Red-FLuc cell lysate were
summarized in this table.
3.4.6 CPP-4-2 downregulated SND1 of breast cancer cells
CPP-4-2 preferentially killed breast cancer cell compared to other cancer
types or normal cell. The mechanism of CPP-4-2 preferentially killing
breast cancer cells was investigated. As shown in Figure 3.13 and Table
3.6, at 30µM CPP-4-2, CPP-4-2Y4A and CPP-4-2Y11A could downregulate
SND1 of MDA-MB-231-GFP-Red-FLuc cells whereas CPP-4-2W10A and
CPP-4-2AAA could not.
To summarize, CPP-4-2 could downregulate SND1 in
MDA-MB-231-GFP-Red-FLuc cells. W10 was the essential amino acid of
CPP-4-2 in SND1 downregulation whereas Y4 and Y11 were not.
115
Figure 3.13 CPP-4-2 downregulated SND1 in
MDA-MB-231-GFP-Red-FLuc cells
MDA-MB-231-GFP-Red-FLuc cells were treated with CPP-4-2 and its mutant peptides
for 24h. The experiment was conducted for more than 3 times and result from one
trial is shown here.
Table 3.6 Cytotoxicity of peptides and their ability to interact with
SND1 or downregulate SND1
Peptide Interaction
with SND1
Cytotoxicity to
MDA-MB-231
-GFP-Red-FLuc
SND1
downregulation
(at 30µM)
CPP-4-2 + + + + +
CPP-4-2Y4A + + + + +
CPP-4-2W10A - - - -
CPP-4-2Y11A + + + + +
CPP-4-2AAA NA - - - -
Cytotoxicity of 4-2 and its mutant peptides towards MDA-MB-231-GFP-Red-FLuc cells,
their ability to interact with SND1 or downregulate SND1 were summarized in this
table. NA: not available
116
Since CPP-4-2 could downregulate SND1 in MDA-MB-231-GFP-Red-FLuc
cells, we tested the effect of CPP-4-2 on other breast cancer cell lines.
Figure 3.14 showed that CPP-4-2 could downregulate SND1 in all of the 3
breast cancer cell lines MDA-MB-231-GFP-Red-FLuc, MCF7 and
MDA-MB-468.
Figure 3.14 CPP-4-2 downregulated SND1 in breast cancer cells
Different cell lines were treated with CPP-4-2 for 24h. The experiment was conducted
for more than 3 times and result from one trial is shown here.
3.4.7 Overexpression of SND1 reduced the cytotoxicity of
CPP-4-2 to breast cancer cells
Since CPP-4-2 could downregulate SND1 of breast cancer cells and was
toxic to breast cancer cells, we wanted to investigate if the
downregulation of SND1 by CPP-4-2 was the reason for breast cancer cell
death. SND1 was overexpressed in breast cancer cell line
MDA-MB-231-GFP-Red-FLuc (Figure 3.15). When SND1 was
overexpressed, the cytotoxicity of CPP-4-2 to breast cancer cells was
117
reduced (Figure 3.16) indicating that CPP-4-2 mediated SND1
downregulation was the possible reason for breast cancer cell death.
Figure 3.15 Overexpression of SND1 in MDA-MB-231-GFP-Red-FLuc cell
SND1 was overexpressed in MDA-MB-231-GFP-Red-FLuc cells according to the
method in methodology. pCMV6-Entry-SND1-cMyc-DDK plasmid was used to
transfect MDA-MB-231-GFP-Red-FLuc cells using lipofectamine 3000. The experiment
was conducted for more than 3 times and result from one trial is shown here.
0 10 20 30 40 500.0
0.5
1.0
1.5
MDA-MB-231-GFP-Red-FLuc
MDA-MB-231-GFP-Red-FLuc-SND1
**
**
CPP-4-2 con. μM
Perc
en
tag
e s
urv
ival
Figure 3.16 SND1 overexpression reduced the cytotoxicity of CPP-4-2 to
MDA-MB-231-GFP-Red-FLuc cells
SND1 was overexpressed in MDA-MB-231-GFP-Red-FLuc cells according to the
method in methodology. pCMV6-Entry-SND1-cMyc-DDK plasmid was used to
transfect MDA-MB-231-GFP-Red-FLuc cells using lipofectamine 3000. Cells were
incubated with serial dilutions of CPP-4-2 in RPMI medium for 72h before MTS assay.
The mean ±S.D. of OD is shown (n=3).
118
3.4.8 CPP-4-2 affected Akt pathway by upregulating p-Akt and
downregulating Akt
CPP-4-2 could downregulate SND1 in breast cancer cells. Since Akt
pathway was reported to be the downstream of SND1 (Rajasekaran et al.,
2016b), the effect of CPP-4-2 on Akt pathway was investigated.
As shown in Figure 3.17, 3.18 and Table 3.7, CPP-4-2, CPP-4-2Y4A and
CPP-4-2Y11A could upregulate p-Akt s473 and downregulate total Akt in
MDA-MB-231-GFP-Red-FLuc cells. CPP-4-2W10A and CPP-4-2AAA could
not upregulate p-Akt s473. The downregulation of total Akt by
CPP-4-2W10A and CPP-4-2AAA was not as significant as the other 3
peptides.
CPP-4-2 could specifically affect Akt pathway in
MDA-MB-231-GFP-Red-FLuc cells. W10 was the essential amino acid of
CPP-4-2 in affecting Akt pathway whereas Y4 and Y11 were not.
119
Figure 3.17 CPP-4-2 specifically affected Akt pathway by upregulating
p-Akt s473 and downregulating total Akt in
MDA-MB-231-GFP-Red-FLuc cells
MDA-MB-231-GFP-Red-FLuc cells were treated with CPP-4-2 and its mutant peptides
for 24h. The experiment was conducted for more than 3 times and result from one
trial is shown here.
0
2
4
6
8
CPP-4-2
CPP-4-2Y4A
CPP-4-2W10A
CPP-4-2Y11A
CPP-4-2AAA
con 30 40 con 30 40 con 30 40 con 30 40 con 30 40 M
a)
pA
kt
S473 e
xp
ressio
n
0.0
0.5
1.0
1.5
CPP-4-2
CPP-4-2Y4A
CPP-4-2W10A
CPP-4-2Y11A
CPP-4-2AAA
con 30 40 con 30 40 con 30 40 con 30 40 con 30 40 M
b)
Akt
exp
ressio
n
Figure 3.18 Quantization of pAkt S473 and Akt expression after
treatment with CPP-4-2
Quantization of pAkt S473 (a) and Akt (b) was performed according to the western
blot results in Figure 3.15. The expression levels of SND1, pAkt S473 and Akt were
normalized to β-actin.
120
Table 3.7 Cytotoxicity of peptides and their ability to interact with
SND1, downregulate SND1 or affect Akt pathway
Peptide Interaction
with SND1
Cytotoxicity to
MDA-MB-231
-GFP-Red-FLuc
SND1
downregulation
(at 30µM)
Upregulation
of pAkt S473
Downregulation
of total Akt
CPP-4-2 + + + + + ↑↑ ↓↓
CPP-4-2Y4A + + + + + ↑↑↑ ↓↓↓
CPP-4-2W10A - - - - ↑ ↓
CPP-4-2Y11A + + + + + ↑↑ ↓↓
CPP-4-2AAA NA - - - - ↑ ↓
Cytotoxicity of 4-2 and its mutant peptides towards MDA-MB-231-GFP-Red-FLuc cells,
their ability to interact with SND1, upregulate pAkt S473 or downregulate total Akt
were summarized in this table. NA: not available
After CPP-4-2 treatment, the expression of p-Akt S473 and total Akt of
different cell lines were tested (Figure 3.19). It was found that CPP-4-2
could upregulate p-Akt s473 and downregulate total Akt in
MDA-MB-231-GFP-Red-FLuc, MCF7, MDA-MB-468 and QGY-7703 cell
lines. In ovary cancer cell line SKOV3, only downregulation of total Akt
was observed. In lung cancer cell line A549-Red-FLuc, only
downregulation of pAkt S473 was observed. For mouse fibroblast L929,
Akt pathway was not affected.
The above data demonstrated that CPP-4-2 preferentially killed breast
cancer compared to other cancer types and normal cells. Here we also
found that Akt pathway in the 3 breast cancer cell lines were all affected
121
by CPP-4-2 whereas less sensitive cell lines such as L929 was not affected
by CPP-4-2. These results suggested that CPP-4-2 preferentially killed
breast cancer cells probably by affecting Akt pathway.
Figure 3.19 CPP-4-2 specifically affected Akt pathway in breast cancer
cells
Different cell lines were treated with CPP-4-2 for 24h before Western blot analysis.
The experiment was conducted for 3 times and result from one trial is shown here.
122
3.4.9 The activation of Akt by CPP-4-2 was transient
CPP-4-2 was found to enhance the phosphorylation of Akt, which might
lead to the activation of its downstream survival promoting pathways.
For this concern, we detect the phosphorylation of Akt by CPP-4-2 in
details. As shown in Figure 3.20, the upregulation of p-Akt S473 was
transient and in long term, there should be no activation of Akt.
10 20 30-2
0
2
4
6
8
10
Akt
pAkt S473
b)
time (h)
Exp
ressio
n
Figure 3.20 The activation of Akt by CPP-4-2 was transient
a) MDA-MB-231-GFP-Red-FLuc cells were treated with CPP-4-2 for different time
before Western blot analysis. The experiment was conducted for 3 times and result
from one trial is shown here. b) Quantization of pAkt S473 and Akt was performed
according to the western blot results in a). The expression levels of SND1, pAkt S473
and Akt were normalized to β-actin.
123
3.4.10 The activation of Akt by CPP-4-2 was not transmitted to
its downstream target mTORC1
Since Akt was a very important hallmark of cell survival and it was
activated after CPP-4-2 treatment. mTORC1 was reported to be one of
the downstream targets of Akt (Manning and Toker, 2017). We wanted to
investigate if the activation of Akt was transmitted to its downstream
target mTORC1. Figure 3.21 showed that there was no significant change
of p-mTOR S2448 after CPP-4-2 treatment, which indicated that the
activation of Akt by CPP-4-2 was not transmitted to its downstream
target mTORC1.
Figure 3.21 CPP-4-2 did not activate mTORC1
MDA-MB-231-GFP-Red-FLuc cells were treated with CPP-4-2 for 24h before Western
blot analysis. The experiment was conducted for 3 times and result from one trial is
shown here.
124
3.4.11 CPP-4-2 mediated degradation of Akt was
proteasome-dependent, the phosphorylation of Akt partially
contributed to the degradation of Akt
Since CPP-4-2 could downregulate SND1 and Akt, we wanted to
investigate if the downregulation of SND1 and Akt by CPP-4-2 was due to
proteasome degradation. Figure 3.22 showed that proteasome inhibitor
MG132 could rescue CPP-4-2 mediated degradation of Akt whereas
MG132 could not rescue CPP-4-2 mediated downregulation of SND1.
Interestingly, when Akt degradation was rescued by MG132, the
phosphorylation of Akt induced by CPP-4-2 was also suppressed, which
indicated that the phosphorylation of Akt might be a feedback of Akt
degradation.
To summarize the degradation of Akt induced by CPP-4-2 was
proteasome dependent whereas the downregulation of SND1 induced
by CPP-4-2 was not. The phosphorylation of Akt might be a feedback of
Akt degradation induced by CPP-4-2.
125
Figure 3.22 CPP-4-2 induced proteasome-dependent degradation of Akt
MDA-MB-231-GFP-Red-FLuc cells were pre-incubated with 5µM of MG132 for 24h
before co-incubation with 30µM of CPP-4-2 peptide in RPMI medium for 24h before
western blot analysis. β-actin was shown as loading control. Cell treatment and
western blot were conducted for 3 times. Result from one trial is shown.
CPP-4-2 could mediate proteasome degradation of Akt and
phosphorylation of Akt in breast cancer cells. We wanted to investigate
the mechanism of Akt degradation. It was reported that p-Akt was a
more preferred substrate for proteasome degradation than Akt (Bae et
al., 2012). PI3K inhibitor LY294002 was used to inhibit the
phosphorylation of Akt (Figure 3.23). When the phosphorylation of Akt
was suppressed by LY294002, Akt degradation was partially rescued,
indicating that the degradation of Akt induced by CPP-4-2 was partially
contributed by the phosphorylation of Akt at S473.
126
Figure 3.23 Akt degradation induced by CPP-4-2 was partially
contributed by the phosphorylation of Akt at S473
MDA-MB-231-GFP-Red-FLuc cells were pre-incubated with 10µM of LY294002 for 2h
before co-incubation with 30µM of CPP-4-2 peptide in RPMI medium for 24h before
western blot analysis. β-actin was shown as loading control. Cell treatment and
western blot were conducted for 3 times. Result from one trial is shown.
127
3.4.12 CPP-4-2 affected important cell survival pathway of
MDA-MB-231-GFP-Red-FLuc cells in proteomics study
In order to study the global effect of CPP-4-2, a proteomics study was
performed to identify the differentially expressed proteins after CPP-4-2
treatment in MDA-MB-231-GFP-Red-FLuc cells. There were 1860
proteins found to be differentially expressed after treating with CPP-4-2,
CPP-4-2W10A or CPP-4-2AAA. A total of 372 proteins were found to be
differently expressed when comparing CPP-4-2 vs. untreated,
CPP-4-2AAA and CPP-4-2W10A group with a P value <0.05. The top 30
(the most upregulated) and bottom 30 (the most downregulated)
proteins were shown in Table 3.8 after ranking (according to the fold
change of the proteins in CPP-4-2 group vs. untreated group). Most of
the proteins were found to be involved in basic cellular functions such as
cytoskeleton formation, mRNA processing, Acetyl-CoA metabolism and
cell migration. Three promising SND1 downstream targets, NF-κB2, p400
and ITGB4 were selected for further validation (Table 3.8). NF-κB
signaling was reported to be the downstream of SND1 (Santhekadur et
al., 2012). P400, E1A-binding protein p400, a tumor suppressor gene
(Samuelson et al., 2005) was found to be upregulated after CPP-4-2
treatment. Sequence of peptide 4-2 showed high similarity to that of
ITGB4 (Integrin, beta 4) (Figure 3.24).
128
Table 3.8 Proteomics study of differentially-expressed proteins after
treatment with CPP-4-2 and its mutants
Gene
accession
Fold change
CPP-4-2/untreated
PCPP-4-2 vs.
untreated
PCPP-4-2 vs.
CPP-4-2AAA
PCPP-4-2 vs.
CPP-4-2W10A
Peptide
count
1 CC125 220.4452 0.0109 0.0107 0.0126 13
2 TSP1 44.7043 0.0011 0.0013 0.0028 9
3 AAMP 36.9075 0.0221 0.0210 0.0241 4
4 H1T 36.2005 0.0081 0.0091 0.0089 5
5 MTCL1 26.8343 0.0003 0.0003 0.0005 23
6 CO3 25.6535 0.0027 0.0026 0.0044 24
7 CAPR2 24.5095 0.0080 0.0089 0.0136 3
8 PRP8 23.8686 0.0210 0.0210 0.0269 31
9 CARF 21.7133 0.0041 0.0038 0.0047 10
10 HBA 18.8369 0.0002 0.0002 0.0014 7
11 CPSF1 18.6850 0.0040 0.0080 0.0443 15
12 ACTN3 18.6073 0.0018 0.0016 0.0015 18
13 LIPA1 17.9625 0.0102 0.0134 0.0367 24
14 NFKB2 17.4986 0.0011 0.0010 0.0010 7
15 ACACA 16.2168 0.0039 0.0040 0.0055 28
16 DVL2 14.6437 0.0000 0.0000 0.0000 8
17 PXDN 13.6041 0.0166 0.0185 0.0194 8
18 GOLP3 12.9939 0.0028 0.0029 0.0084 4
19 NU160 12.9299 0.0002 0.0002 0.0008 12
20 SMTN 12.6924 0.0015 0.0012 0.0012 13
21 UBR5 12.1336 0.0000 0.0000 0.0001 22
22 SRCAP 11.6398 0.0005 0.0005 0.0011 23
23 PIEZ1 11.1430 0.0028 0.0024 0.0029 17
24 ATP7A 11.1043 0.0000 0.0001 0.0033 15
25 DSG2 11.0559 0.0062 0.0056 0.0075 10
26 ROCK2 10.9489 0.0067 0.0065 0.0243 22
27 TCPW 10.7468 0.0058 0.0084 0.0248 11
28 ARAP3 10.5210 0.0019 0.0024 0.0053 11
29 EP400 10.2308 0.0003 0.0002 0.0004 21
30 IF4G3 10.0832 0.0037 0.0028 0.0049 19
… …
188 SND1 0.3630 0.0002 0.0033 0.0022 22
… …
212 ITB4 0.3138 0.0370 0.0304 0.0132 17
… …
129
343 BDP1 0.1216 0.0161 0.0003 0.0355 25
344 PRDX1 0.1213 0.0222 0.0121 0.0095 13
345 GEMI5 0.1206 0.0063 0.0001 0.0088 11
346 TCPD 0.1176 0.0032 0.0452 0.0027 20
347 HAP28 0.1173 0.0425 0.0008 0.0376 6
348 HNRPF 0.1165 0.0006 0.0030 0.0071 13
349 CYBP 0.1164 0.0014 0.0054 0.0056 9
350 DPP3 0.1134 0.0007 0.0002 0.0001 5
351 RM12 0.1118 0.0018 0.0017 0.0417 7
352 DCTN2 0.1065 0.0088 0.0047 0.0245 9
353 SYK 0.1060 0.0139 0.0160 0.0359 11
354 CPIN1 0.1011 0.0117 0.0012 0.0024 6
355 HSPB1 0.0949 0.0008 0.0034 0.0044 7
356 P5CS 0.0891 0.0050 0.0069 0.0093 10
357 DUS12 0.0832 0.0004 0.0012 0.0256 4
358 CCAR2 0.0797 0.0013 0.0011 0.0116 8
359 CALR 0.0764 0.0193 0.0304 0.0044 13
360 HNRPR 0.0737 0.0047 0.0249 0.0058 13
361 GAK6 0.0730 0.0248 0.0083 0.0306 8
362 ACTZ 0.0712 0.0063 0.0265 0.0155 6
363 RPR1B 0.0684 0.0001 0.0153 0.0286 7
364 THOC4 0.0637 0.0048 0.0185 0.0024 12
365 SYDC 0.0605 0.0123 0.0271 0.0019 18
366 TOM70 0.0445 0.0181 0.0138 0.0147 9
367 AAAS 0.0342 0.0000 0.0163 0.0107 3
368 AL7A1 0.0335 0.0027 0.0109 0.0007 10
369 UBP2L 0.0287 0.0035 0.0079 0.0410 8
370 PPIB 0.0231 0.0394 0.0007 0.0328 6
371 EIF3M 0.0149 0.0010 0.0283 0.0003 7
372 EIF3L 0.0135 0.0035 0.0210 0.0008 9
MDA-MB-231-GFP-Red-FLuc cells were incubated with 30µM of CPP-4-2,
CPP-4-2W10A or CPP-4-2AAA for 24h before proteomics study. A total of 372
proteins were found to be differentially expressed (PCPP-4-2 vs. untreated<0.05, PCPP-4-2 vs.
CPP-4-2AAA<0.05 and PCPP-4-2 vs. CPP-4-2W10A<0.05). The 372 proteins were ranked according
to the fold change of the proteins in CPP-4-2 group vs. untreated group. The top 30
(most upregulated) and bottom 30 (most downregulated) proteins were shown in
this table. The highlighted proteins were promising SND1 downstream targets and
SND1 which were selected for further validation.
130
Figure 3.24 Sequence alignment of peptide 4-2 to ITGB4
Sequence alignment of peptide 4-2 was conducted with NCBI BLAST. ITGB4 showed
highest similarity to peptide 4-2 among proteins from mammalian cells. Sequence ID
of ITGB4 isoform X1 (Homo sapiens): XP_006721929.1.
Among the 372 differentially expressed proteins, pathway analysis was
conducted to cluster these proteins. The top 8 pathways that were most
probably affected by CPP-4-2 were shown in Figure 3.25. These pathways
were all essential cell-survival associated pathways, including tRNA
charging, actin cytoskeleton signaling, .regulation of eIF4 and p70S6K
signaling, protein ubiquitination pathway, EIF2 signaling, sirtuin signaling
pathway, mTOR signaling and caveolar mediated endocytosis signaling.
131
tRNA C
hargin
g
Act
in C
ytosk
elet
on Sig
nalin
g
Reg
ulatio
n of e
IF4
and p
70S6K
Sig
nalin
g
Pro
tein
Ubiq
uitinat
ion P
athw
ay
EIF
2 Sig
nalin
g
Sirt
uin S
ignal
ing P
athw
ay
mTO
R S
ignal
ing
Cav
eola
r-m
edia
ted E
ndocyto
sis
Sig
nalin
g
0
2
4
6
8
10
-lo
g(p
-valu
e)
Figure 3.25 Top 8 pathways most probably affected by CPP-4-2
determined by proteomics study
MDA-MB-231-GFP-Red-FLuc cells were incubated with 30µM of CPP-4-2,
CPP-4-2W10A or CPP-4-2AAA for 24h before proteomics study. A total of 372
proteins were found to be differentially expressed (PCPP-4-2 vs. untreated<0.05, PCPP-4-2 vs.
CPP-4-2AAA<0.05 and PCPP-4-2 vs. CPP-4-2W10A<0.05). After pathway analysis with IPA, the top
8 pathways most probably affected by CPP-4-2 were shown. –log (p-value)
represented the probability of one pathway affected by CPP-4-2. Cell treatment with
peptides was conducted in triplicate. Mass spectrometry analysis was conducted in
triplicate.
132
3.4.13 CPP-4-2 upregulated pro-apoptotic NF-κB2 but did not
affect EP400 or ITGB4
Among the 372 differentially expressed proteins, ITGB4, EP400 and
NF-κB2, as promising downstream targets of SND1 were selected for
further validation. Real-time PCR was performed to determine the mRNA
level of these genes. No significant difference was detected in the mRNA
level of ITGB4 or EP400 after CPP-4-2 treatment (Figure 3.26). The
protein levels of EP400 and ITGB4 remained unknown.
EP400
con
CPP-4
-2
CPP-4
-2W
10A
CPP-4
-2Y11
A
0.0
0.5
1.0
1.5
2.0con
CPP-4-2
CPP-4-2W10A
CPP-4-2Y11A
a)
mR
NA
NS
NS NS
ITGB4
con
CPP
-4-2
CPP
-4-2
W10
A
CPP
-4-2
Y11
A
0.0
0.5
1.0
1.5
2.0con
CPP-4-2
CPP-4-2W10A
CPP-4-2Y11A
b)
mR
NA NS
NSNS
Figure 3.26 CPP-4-2 did not change the mRNA levels of EP400 or ITGB4
MDA-MB-231-GFP-Red-FLuc cells were treated with 30µM of CPP-4-2 or its mutant
peptides for 24h before RNA extraction. mRNA levels of EP400 and ITGB4 were
determined by real-time PCR. The mean ±S.D. of fold change of mRNA is shown here
(n=3). NS: not significant, p>0.05.
133
Interestingly, NF-κB2 mRNA was significantly upregulated after CPP-4-2
treatment compared with untreated control, CPP-4-2W10A or
CPP-4-2AAA (Figure 3.27a). The cytotoxic mutant, CPP-4-2Y4A could also
enhance the transcription of NF-κB2 to the similar extent as CPP-4-2,
whereas the other cytotoxic mutant CPP-4-2Y11A could not.
Since NF-κB2 was a member of NF-κB family, the expression of other
NF-κB family members NFkB1 and RelA was also tested. Even though
both NF-κB1 and RelA genes showed similar trend as NF-κB2 after
peptide treatment, there was no statistically significant difference of the
mRNA levels of NF-κB1 and RelA among different peptide treatment
groups (Figure 3.27b and c).
134
con
CPP-4
-2
CPP-4
-2Y4A
CPP-4
-2W
10A
CPP-4
-2Y11
A
CPP-4
-2AAA
0
2
4
6
8con
CPP-4-2
CPP-4-2Y4A
CPP-4-2W10A
CPP-4-2Y11A
CPP-4-2AAA
***
***
NS NS
NS
NF-κB2a)
mR
NA
NF-κB1
con
CPP
-4-2
CPP
-4-2
Y4A
CPP
-4-2
W10
A
CPP
-4-2
Y11
A
CPP
-4-2
AAA
0.0
0.5
1.0
1.5
2.0con
CPP-4-2
CPP-4-2Y4A
CPP-4-2W10A
CPP-4-2Y11A
CPP-4-2AAA
b)
NSNS
NS NS
NS
mR
NA
RelA
con
CPP-4
-2
CPP-4
-2Y4A
CPP-4
-2W
10A
CPP-4
-2Y11
A
CPP-4
-2AAA
0.0
0.5
1.0
1.5con
CPP-4-2
CPP-4-2Y4A
CPP-4-2W10A
CPP-4-2Y11A
CPP-4-2AAA
c)
NSNS
NS NS
NS
mR
NA
Figure 3.27 CPP-4-2 upregulated mRNA levels of NF-κB2 and its family
members
MDA-MB-231-GFP-Red-FLuc cells were treated with 30µM of CPP-4-2 or its mutant
peptides for 24h before RNA extraction. mRNA levels of NF-κB2, NF-κB1 and RelA
were determined by real-time PCR. The mean ±S.D. of fold change of mRNA is shown
here (n=3). ***p<0.001 compared with control; NS: not significant, p>0.05.
135
Since CPP-4-2 peptide could induce apoptosis in flow cytometry assay,
we investigated if CPP-4-2 induced apoptosis through Bax/BCL2 signaling.
As shown in Figure 3.28 a, no significant difference was observed in the
mRNA levels of Bax after CPP-4-2 treatment. The mRNA level of BCL2
was found to be upregulated by CPP-4-2, which was opposite to the
expected results (Figure 3.28 b). The protein levels of Bax and BCL2
remained unknown.
con
CPP-4
-2
CPP-4
-2Y4A
CPP-4
-2W
10A
CPP-4
-2Y11
A
CPP-4
-2AAA
0.0
0.5
1.0
1.5con
CPP-4-2
CPP-4-2Y4A
CPP-4-2W10A
CPP-4-2Y11A
CPP-4-2AAA
Bax
NS NS
NS NSNS
a)
mR
NA
BCL2
con
CPP
-4-2
CPP
-4-2
Y4A
CPP
-4-2
W10
A
CPP
-4-2
Y11
A
CPP
-4-2
AAA
0.0
0.5
1.0
1.5
2.0con
CPP-4-2
CPP-4-2Y4A
CPP-4-2W10A
CPP-4-2Y11A
CPP-4-2AAA
NSNS
NS
b)
mR
NA
Figure 3.28 mRNA levels of Bax and BCL2 after peptide treatment
MDA-MB-231-GFP-Red-FLuc cells were treated with 30µM of CPP-4-2 or its mutant
peptides for 24h before RNA extraction. mRNA levels of Bax and BCL2 were
determined by real-time PCR. The mean ±S.D. of fold change of mRNA is shown here
(n=3). NS: not significant, p>0.05.
136
3.4.14 In silico docking of peptide 4-2 to SN1/2
In silico docking of peptide 4-2 to SN1/2 was conducted in Prof. Ruben
Abagyan’s lab using ICM (Internal Coordinate Mechanics) (Abagyan and
Totrov, 1994). Sincere thanks are given to Prof. Ruben Abagyan and his
PhD student Mr. Da Shi.
Five tentative binding sites (colored spaces) on SN1/2 identified by
PocketFinder were shown in Figure 3.29. One box, Box1 was
demonstrated as an example of the box space region around Pocket1
(Figure 3.29).
Figure 3.29 Five tentative binding sites on SN1/2 and Box1
Tentative binding sites (the 5 colored spaces) on SN1/2 were identified by
PocketFinder. Box1, defined as box space region around Pocket1 was shown as an
example. The blue helix protein structure was the crystal structure of SN1/2 domain
of SND1 (PDB: 4QMG).
In silico docking of peptide 4-2 was performed with W10 (the essential
amino acid in the activity of CPP-4-2) restrained in Box1-5, Boxi and
137
Boxno, respectively. As a result, 3200 conformations in each box were
output as possible conformations of 4-2 interacting with SN1/2.
The docking scores of 2 conformations in Box1, 1 conformation in Box4,
3 conformations in Boxno and 15 conformations in Boxi were ≤-190
(Table 3.9). There were 3 very similar conformations of peptide 4-2
(overlapping helix-like structures in Figure 3.30 b) identified from Boxi
(Figure 3.30 a), besides which no other conformations of any similarities
were identified among the 21 conformations (Table 3.9). As a result, the
overlapping helix-like structure shown in Figure 3.24b was the most
possible conformation of peptide 4-2 interacting with SN1/2.
Table 3.9 Possible conformations of peptide 4-2 binding to SN1/2
Box No. No. of conformations
with docking score ≤-190
Features of the
conformations with
docking score ≤-190
Box1 2 ADC
Box2 0 ADC
Box4 1 ADC
Box5 0 ADC
Box6 0 ADC
Boxno 3 ADC
Boxi 15 SC*3
Lower docking score meant better binding in ICM. ADC: all different conformations;
SC: similar conformations.
138
Figure 3.30 Most possible conformation of 4-2 interacted with SN1/2
The orange linear peptide structure was MTDH 11-mer peptide nested in the binding
groove of SND1-MTDH interface; The big blue structure was SN1/2 domain of SND1
(PDB: 4QMG). a) The purple box was boxi encompassing the space region around
SND1-MTDH interface; b) The yellow, pink and green overlapping helix-like structure
was the most possible conformation of peptide 4-2 interacting with SN1/2;
139
3.5 Discussion
3.5.1 Construction of CPP-4-2 peptide
TAT CPP was selected for directing 4-2 and 4-8 peptides into mammalian
cells because it had high cell penetrating efficiency and low cytotoxicity.
Unfortunately, TAT-4-2 and TAT-4-8 peptides induced precipitation in cell
culture medium probably due to their low isoelectric point (pI) values. As
a consequence, two more arginines were added before TAT to produce a
hybrid CPP, RR-TAT to solve the problem of solubility by increasing pI
while to increase cell penetrating efficiency.
However, RR-TAT-4-8 peptide still induced great precipitation in tissue
culture medium. This peptide was suspended for further assay.
3.5.2 In silico docking of peptide 4-2 to SN1/2
SND1-interacting peptide 4-2 could disrupt SND1-MTDH interaction.
W10 was found to be the essential amino acid in the activity of peptide
4-2, including cytotoxicity, SND1 interaction, SND1 downregulation, Akt
degradation and activation of NF-κB2. In silico docking of peptide 4-2 to
SN1/2 was performed to explain the importance of W10 in SND1
interaction. We wanted to predict the binding site of 4-2 on SN1/2 and
also to know if the binding site was SND1-MTDH interface.
There were 3 very similar conformations of peptide 4-2 identified in Boxi
140
(Figure 3.30b, helix-like structure), besides which no other
conformations of any similarities were identified in the 21 conformations
with docking score≤-190. This result suggested that the helical structure
of peptide 4-2 was close to but not at the interface of SND1-MTDH,
which might explain the inconsistency of the disruption of MTDH-SND1
by peptide 4-2 in different assays.
Docking study suggested that peptide 4-2 adopted a helical structure and
interacted with SN1/2 near the binding interface of SND1-MTDH
complex. The peptide motif shown in the co-crystal structure of
SND1-MTDH was an 11-mer MTDH peptide motif (Figure 2.2, PDB:
4QMG), which was shorter than the 22-mer MTDH peptide which was
used in the peptide ELISA assay and much shorter than the MTDH
full-length protein. This indicated that there was unknown structure of
MTDH, which might be disrupted by peptide 4-2.
3.5.3 MTS, Flow cytometry and high content screening
MTS and flow cytometry methods were used in this project to measure
the cytotoxicity of peptides to breast cancer cells. MTS is a standard
method through measuring the metabolic activity of the cells to
represent the number of viable cells. Flow cytometry is another standard
method to measure the flip of phosphatidylserine from the inner surface
of cell membrane to the outer surface and also cell permeability to
141
represent the viability of living cells. These two methods are two
standard methods but with different principles, which are used in this
project to double confirm the cytotoxicity of peptide 4-2 to breast cancer
cells.
More powerful methods for drug screening have been developed such as
high content screening. In order to test the activity of thousands of
compounds, high-content screening is a better choice. The microscope
can capture the image of cells and output multiple phenotypes of cells at
one time. Thousands of compounds can be tested in parallel for their
activity at the same time. So high content screening is very efficient and
powerful for high-throughput screening.
3.5.4 CPP-4-2 preferentially killed breast cancer cells but not
other cancer types or mouse fibroblast
There are different subtypes of breast cancer according to different
classification criteria as introduced in the introduction. According to the
receptor status, breast cancer can be classified into luminal, HER2
overexpression, basal and normal-like subtypes of breast cancer (Dai et
al., 2015). Basal subtype or triple negative breast cancer was the most
difficult to treat due to the missing of ER, PR and HER2 receptors. In our
study, we chose 2 triple negative breast cancer cell line, MDA-MB-231
and MDA-MB-468 to represent triple negative breast cancer (Subik et al.,
142
2010). We also used MCF7, which had ER and PR receptors to represent
luminal A subtype of breast cancer (Subik et al., 2010) to further expand
the scope of our study. In our initial thought, we used QGY-7703 to
represent liver cancer cell line, which was found to be Hela derivative,
warning us of proper choosing of cell lines for cancer study and drug
screening.
CPP-4-2 peptide preferentially killed breast cancer cells,
MDA-MB-231-GFP-Red-FLuc, MCF7 and MDA-MB-468 but not ovary
cancer cell SKOV3, Hela derivative QGY-7703, lung cancer cell A549 or
mouse fibroblast L929. One possible reason was that CPP-4-2 had
different cell penetration efficiency in these cell lines. Peptide
accumulation assay indicated that peptide accumulation in different cell
lines were similar. More likely, CPP-4-2 affected a unique
SND1-dependent pathway which was specific and essential to the
survival of breast cancer cells probably the SND1-dependent Akt
pathway. Targeting SND1 and its potential binding partner by CPP-4-2
might be a treatment specific to breast cancer.
3.5.5 CPP-4-2 mediated SND1-dependent cytotoxicity in
MDA-MB-231-GFP-Red-FLuc cells
Y and W were the hydrophobic amino acids enriched in the peptide
sequences after phage display screening. Y4 and W10 in peptide 4-2 had
143
a distance of 5 (Y4 and Y11 had the distance of 6) amino acids in
between, which corresponded to the sequence pattern of MTDH peptide
that interacted with SND1. Results from mutagenesis experiments
confirmed that W10 of peptide 4-2 was essential in mediating
cytotoxicity and interacting with SND1. Mutation of W to A in position 10
(CPP-4-2W10A) abolished its cytotoxicity and its ability to interact with
SND1. This result suggested that CPP-4-2 mediated an SND1-dependent
cytotoxicity in MDA-MB-231-GFP-Red-FLuc cells.
3.5.6 Peptide 4-2 mediated disruption of SND1-MTDH
interaction and subsequent degradation of SND1 might be the
reason for breast cancer cell death
Peptide 4-2 was demonstrated to compete with the binding of 22-mer
MTDH peptide to SN1/2 domain of SND1. Peptide 4-2 could also disrupt
full-length SND1-MTDH complex in co-IP assay (Chapter 2). It was
reported that the disruption of SND1-MTDH interaction by mutagenesis
would result in the suppression of mammosphere formation in vitro and
tumor initiation in vivo (Wan et al., 2014). And the mechanism was
proposed to be when MTDH-SND1 interaction was disrupted, MTDH
could no longer protect SND1, which resulted in the degradation of SND1
(Wan et al., 2014). In our result, peptide 4-2 could disrupt SND1-MTDH
interaction, which probably lead to the degradation of SND1. Besides,
144
overexpression of SND1 could reduce the cytotoxicity of peptide 4-2 to
breast cancer cells. These results suggested that the disruption of
SND1-MTDH interaction and subsequent degradation of SND1 by
peptide 4-2 might be the reason for breast cancer cell death (Figure
3.31).
3.5.7 CPP-4-2 might kill breast cancer cells by affecting Akt
pathway or by enhancing NF-κB2 transcription
The abilities of CPP-4-2 and its mutant peptides in exerting cytotoxicity,
interacting with SND1, downregulating SND1, affecting Akt pathway and
upregulating NF-kB2 were summarized in Table 3.10. CPP-4-2,
CPP-4-2Y4A and CPP-4-2Y11A were found to be toxic to breast cancer
cell MDA-MB-231-GFP-Red-FLuc. Consistently, they were also
demonstrated to affect Akt pathway, upregulate NF-κB2 and interact
with SND1 (the upregulation of NF-κB2 by CPP-4-2Y11A was not
significant). CPP-4-2W10A, which was found to be non-toxic to
MDA-MB-231-GFP-Red-FLuc could not affect Akt pathway, interact with
SND1 or upregulate NF-kB2.
145
Table 3.10 A summary of the characteristics of CPP-4-2 and its mutants
Peptide Interacting
with SND1
(Peptide
pull-down
assay)
Cytotoxicity
to
MDA-MB-231
-GFP-Red-FLuc
SND1
downregulation
(at 30µM)
Affecting
Akt
pathway
NF-kB2
regulation
CPP-4-2 + + + + +
CPP-4-2Y4A + + + + +
CPP-4-2W10A - - - - -
CPP-4-2Y11A + + + + -
CPP-4-2AAA NA - - - -
This table summarized the ability of CPP-4-2 and its mutant peptides to interact with
SND1, kill MDA-MB-231-GFP-Red-FLuc cells, affect Akt pathway and upregulate
NF-κB2. The SND1-interacting ability of the peptides was determined by peptide
pull-down assay. NA: not available
3.5.7.1 CPP-4-2 induced cytotoxicity probably through Akt pathway
Akt pathway was reported to be the downstream of SND1 (Rajasekaran
et al., 2016b). Since Akt pathway played a very essential role in cell
survival, the significant downregulation of total Akt might be one of the
reasons for cell death. Akt could be degraded by ubiquitin
proteasome-dependent pathway, caspase-mediated cleavage, or
caspase-dependent ubiquitination (Liao and Hung, 2010). Interestingly,
pAkt S473 was a more preferred substrate than Akt for ubiquitination by
E3 ubiquitin ligase MULAN. The degradation of Akt by MULAN could
146
suppress cell proliferation and viability (Bae et al., 2012). In our result,
peptide 4-2 induced degradation of Akt, which was partially contributed
by the phosphorylation of Akt. The degradation of Akt might be
mediated by E3 ubiquitin ligase MULAN. And MULAN-mediated
degradation of Akt might be the reason for breast cancer cell death
induced by peptide 4-2.
Besides, X-linked inhibitor of apoptosis protein (XIAP) regulated
apoptosis through PI3K/Akt pathway, which involved caspase cleavage
(Asselin et al., 2001). Caspase-dependent cleavage of many specific
proteins might turn off survival pathways including PI3K/Akt pathway,
which might otherwise interfere with the apoptotic response (Widmann
et al., 1998). As a result, the downregulation of Akt induced by CPP-4-2
in breast cancer cells might be the reasons for cell death (Figure 3.31).
3.5.7.2 CPP-4-2 killed breast cancer cells probably by enhancing the
transcription of NF-κB2
NF-κB2/p100 was reported to promote apoptosis through its death
domain. When p100 lost its death domain by being processed to p52,
the tumorigenic activity was elevated (Wang et al., 2002). This suggested
a pro-apoptotic role of p100 (not p52) in promoting cancer cell death.
NF-κB2 was considered as a direct activator of programmed cell death
(Hacker and Karin, 2002). The expression of p100 profoundly sensitized
147
cells to death-receptor-mediated apoptosis through an IκB-independent
pathway (Wang et al., 2002).
In our experiments, significant upregulation of NF-κB2 instead of NF-κB1
or RelA by CPP-4-2 indicated a specific activation of NF-κB2 gene instead
of the whole NF-κB pathway. The elevated pro-apoptotic activity of the
death domain of p100 induced by CPP-4-2 peptide might lead to the
death of the cells. It was possible that the acute accumulation of p100,
which was not processed into p52 might lead to the death of breast
cancer cells. This hypothesis could be validated through detecting both
of the protein levels of p100 and p52 after CPP-4-2 treatment in the
future experiments. NF-κB2 was reported to induce apoptosis through
activating caspase-8 (Wang et al., 2002) and probably subsequent
caspase-3. To summarize, CPP-4-2 might induce apoptosis of breast
cancer cells by enhancing the transcription of NF-κB2 (Figure 3.31).
Besides, Akt has already been demonstrated to be a direct substrate of
caspase in apoptotic cells. The Asp-462 of Akt1 was determined as the
primary cleavage site and a 43kD cleaved product (N-terminal of Akt
product) was produced (Xu et al., 2002). Unfortunately, the Akt antibody
used in our experiments could only recognize the C-terminal of Akt
protein, which could not recognize the possible cleaved Akt product. The
signigicant degradation of total Akt induced by CPP-4-2 peptide might be
due to the NF-κB2 mediated activation of caspase cascade.
148
Figure 3.31 A proposed pathway of peptide 4-2 mediating breast cancer
cell death
Based on the results in our experiments, we hypothesized a pathway probably
through which CPP-4-2 killed breast cancer cells. In untreated breast cancer cells,
SND1 can interact with MTDH so breast cancer cell will survive. When peptide 4-2 is
added onto breast cancer cells, it will interact with SND1 and disrupts SND1-MTDH
interaction, which probably leads to the degradation of SND1. The degradation of
SND1 might result in the phosphorylation and degradation of Akt, which leads to the
apoptosis of breast cancer cell. On the other hand, the disruption of SND1-MTDH
interaction by peptide 4-2 might enhance the transcription of NF-κB2, which leads to
the apoptosis of breast cancer cell.
149
Chapter 4 Limitations and Future
perspectives
4.1 A novel SND1-interacting peptide that can disrupt
SND1-MTDH interaction
In this study, we identified a novel SN1/2 interacting peptide 4-2 using
phage display. We have successfully demonstrated that peptide 4-2 could
interact with SND1 and disrupt SND1-MTDH interaction, which probably
lead to the degradation of SND1. A novel way to disrupt SND1-MTDH
interaction was identified in this study. Besides MTDH there are also
many other SND1-interacting partners, which are listed in Table 4.1.
150
Table 4.1 SND1 binding partners
name Binding domains in
SND1
Functions Publications
MTDH SN1/2 domain
Binding to 384-407 of
MTDH
Oncoprotein (Wan et al., 2014)
Ago2 SN domian Essential component of RISC (Caudy et al., 2003b)
CBP SN domain binding to
1099-1758 of CBP
Transcriptional coactivator (Valineva et al., 2005)
STAT6 SN domain binding to
TAD domain of STAT6
Transcription factor (Yang et al., 2002)
G3BP SN domain Marker and effector of stress
granules
(Gao et al., 2010)
MGLL SN domain Monoglyceride lipase, tumor
suppressor gene
(Rajasekaran et al., 2016a)
syt11 Binding to N-terminal
tandem repeats of
syt11C2B
Calcium-sensitive members
in the regulation of
post-Golgi traffic
(Milochau et al., 2014b)
PC1 Bind to the C-terminus
of PC-1
Associated with kidney
disease
(Low et al., 2006)
Pim-1 NA Proto-oncogene (Leverson et al., 1998)
SAM68 NA Splicing factor (Cappellari et al., 2014)
SND1 was reported as a binding partner of multiple proteins. SN1/2 domain of SND1
was used as a bait to screen out SND1 binding peptide in our project. However, SND1
was reported to be interacting with multiple binding partners through SN1/2 domain.
NA: not available
SND1 could form complex with many partners, such as MTDH (Wan et al.,
2014), Ago2 (Caudy et al., 2003b), CBP (Valineva et al., 2005), STAT6
(Yang et al., 2002), PC1 (Low et al., 2006), Pim-1 (Leverson et al., 1998),
G3BP (Gao et al., 2010), SAM68 (Cappellari et al., 2014), syt11 (Milochau
et al., 2014a) and MGLL (Rajasekaran et al., 2016b). Publications
151
reporting the interactions between these binding partners and SND1
were listed in Table 4.1.
In the initial hypothesis of this project, we proposed that the SND1
interacting peptides identified from phage display would disrupt the
interaction of SND1 with MTDH. This hypothesis was based on the fact
that the bait used in phage display screening was SN1/2 domain of SND1,
which was involved in SND1-MTDH interaction. Besides, the binding
interface of MTDH to SND1 was well characterized as a binding groove
with two hydrophobic binding pockets on SND1 (Guo et al., 2014), and
therefore as a potential binding site for interacting with peptide. In fact,
SND1 had so many binding partners, which could also be affected by
peptide 4-2 (Table 4.1), which became the limitation of this project.
4.2 Peptide 4-2 shows preferential cytotoxicity towards breast
cancer cells
The novel SND1-interacting peptide 4-2 is preferentially toxic to breast
cancer cells. The IC50s of peptide 4-2 to breast cancer cells are
15.9-22.4µM, which are high for in vivo efficacy study. Optimization of
peptide 4-2 is necessary before in vivo efficacy study. We have identified
1 amino acid W10, which is essential in the cytotoxicity of peptide 4-2.
We may change this W to other hydrophobic amino acid to see if it can
increase its affinity to SND1 and subsequent cytotoxicity to breast cancer
152
cells. Other optimization strategy could also be used such as cyclization
of peptide 4-2, changing L-form amino acid to D-form amino acid or
introducing peptide 4-2 into nanoparticles.
Peptide 4-2 kills breast cancer cells by inducing apoptosis, which is one
common mechanism of anti-cancer drug to suppress cancer growth.
Another mechanism of inhibiting cancer progression is inducing cell cycle
arrest, for example doxorubicin can induce cell cycle arrest by
suppressing G2/M transition (Ling et al., 1996). It is better to combine
these two mechanisms, inducing apoptosis and cell cycle arrest to treat
cancer. As a result, in our future in vivo efficacy experiment we can
combine the apoptosis-inducing peptide 4-2 with doxorubicin, which can
induce cell cycle arrest as a combination therapy to treat breast cancer.
4.3 Mechanisms of the cytotoxicity of peptide 4-2 to breast
cancer cells
Mechanism investigation of the cytotoxicity of peptide 4-2 to breast
cancer cell suggested that peptide 4-2 could interact with SND1 and
disrupt SND1-MTDH interaction, which probably lead to the degradation
of SND1. Overexpression of SND1 could reduce the cytotoxicity of
peptide 4-2 to breast cancer cells, indicating that the downregulation of
SND1 induced by peptide 4-2 was the possible reason for breast cancer
cell death. Further investigation on the downstream pathway of SND1
153
suggested that on one hand, peptide 4-2 could induce the degradation of
Akt, which was partially contributed by the phosphorylation of Akt. On
the other hand, peptide 4-2 could enhance the transcription of NF-κB2.
But whether the degradation of Akt by peptide 4-2 and the enhanced
transcription of NF-κB2 by peptide 4-2 are mediated through SND1 are
unknown.
It was reported that the overexpression of E3 ubiquitin ligase MULAN
could result in the degradation of Akt and suppression of cell
proliferation and cell viability (Bae et al., 2012). And it was also reported
that NF-κB2/p100 had pro-apoptotic function by inducing apoptosis
through activating caspase-8 (Wang et al., 2002). These two are the
possible mechanisms which lead to breast cancer cell death. But
whether peptide 4-2 mediated death of breast cancer cells are through
these two pathways needs further validation. MG132, which could
inhibit Akt degradation and caspase-8 inhibitor could be used to top Akt
degradation and caspase-8 cascade to protect breast cancer cell from the
death induced by peptide 4-2 in future experiments.
4.4 W10 is the essential amino acid in the activity of peptide
4-2
The SND1-interacting peptides showed increased frequency of W and Y
after phage display screening. In the subsequent experiments, W10 was
154
found to be the essential amino acid in cytotoxicity, SND1-interaction,
SND1 downregulation, Akt degradation and NF-κB2 activation. We used
molecular docking to determine the configuration of peptide 4-2 on
SN1/2 and found out that peptide 4-2 bound to a binding site near the
binding interface of SND1-MTDH. Moreover, the essential amino acid
W10 was facing outward to the binding interface of peptide 4-2 and
SN1/2. It was difficult to explain the importance of W10 in the direct
interaction of peptide 4-2 with SN1/2. W10 might work as an essential
amino acid in maintaining the secondary structure of peptide 4-2 for
interacting with SND1. In order to investigate the binding site of peptide
4-2 on SND1, different motif of SN1/2 could be expressed or synthesized
to interact with peptide 4-2 in binding assays in the future.
155
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